model/dict.json

{
    "MDC": [
      "metering data collector",
      "mobile data challenge",
      "multiple description coding"
    ],
    "SVM": [
      "support vector machine",
      "state vector machine"
    ],
    "MER": [
      "maximum entropy regularizer",
      "music emotion research",
      "music emotion recognition"
    ],
    "SVC": [
      "support vector classifier",
      "scalable video coding"
    ],
    "CNN": [
      "convolutional neural network",
      "condensed nearest neighbor",
      "complicated neural networks",
      "citation nearest neighbour"
    ],
    "FEC": [
      "forward error correction",
      "federal election candidate"
    ],
    "FSM": [
      "finite state machine",
      "fast sweeping method"
    ],
    "LDA": [
      "latent dirichlet allocation",
      "linear discriminant analysis"
    ],
    "FR": [
      "frame recall",
      "faster r - cnn",
      "fooling rate"
    ],
    "TF": [
      "term frequency",
      "trend filtering",
      "tensor factorization",
      "transcription factor"
    ],
    "SS": [
      "speech synthesis",
      "single stage",
      "stochastic search",
      "social status",
      "spectrum sensing",
      "severe sepsis",
      "scheduled sampling",
      "secondary structure",
      "simple sum"
    ],
    "GPS": [
      "global positioning system",
      "general pattern search",
      "generalized propensity score"
    ],
    "PCA": [
      "principal component analysis",
      "posterior cortical atrophy"
    ],
    "MSE": [
      "mean squared error",
      "model selection eqn",
      "minimum square error"
    ],
    "ILP": [
      "inductive logic programming",
      "integer linear programming"
    ],
    "MTI": [
      "mixture time invariant",
      "medical text indexer"
    ],
    "SNN": [
      "siamese neural network",
      "spiking neural networks"
    ],
    "SOP": [
      "sentence order prediction",
      "secrecy outage probability"
    ],
    "SVD": [
      "singular value decomposition",
      "singing voice detection"
    ],
    "CD": [
      "cosine distance",
      "contrastive divergence",
      "consecutive disks",
      "critical difference",
      "chamfer distance",
      "contact distance",
      "cover difference",
      "chemical diagram",
      "crohn 's disease"
    ],
    "OCR": [
      "optical character recognition",
      "one - to - one character replacements"
    ],
    "MRC": [
      "machine reading comprehension",
      "maximal ratio combining",
      "magnetic resonance coupling"
    ],
    "SAP": [
      "stable abstraction principle",
      "simple amplitude presitortion"
    ],
    "DPP": [
      "determinantal point process",
      "disjoint paths problem"
    ],
    "QRF": [
      "quantile random forest",
      "quantile regression forest"
    ],
    "GCM": [
      "google cloud messaging",
      "generalized cell - to - cell mapping",
      "general circulation model",
      "galois / counter mode",
      "global circulation model"
    ],
    "PPP": [
      "poisson point process",
      "palm point process"
    ],
    "FCN": [
      "fully convolutional neural network",
      "fully connected network"
    ],
    "RNN": [
      "recurrent neural network",
      "random neural networks",
      "recursive neural network",
      "reverse nearest neighbour"
    ],
    "ML": [
      "machine learning",
      "maximum likelihood",
      "model logic",
      "malware landscape",
      "mortar luminance"
    ],
    "BC": [
      "bandwidth constraint",
      "betweenness centrality",
      "between class",
      "broadcast channel",
      "blockchain"
    ],
    "BN": [
      "bayesian network",
      "batch normalization"
    ],
    "TC": [
      "telephone conversations",
      "town crier",
      "tumor core",
      "time - continuous",
      "target country",
      "total cover",
      "traffic class",
      "total correlation"
    ],
    "TS": [
      "tree structures",
      "terminal stance",
      "temperature scaling",
      "temperature - based sampling",
      "tabu search",
      "thompson sampling",
      "time series",
      "time switching",
      "target syntactic",
      "text summarization",
      "triadic simmelian",
      "tessellation shader"
    ],
    "HPC": [
      "high performance computing",
      "hardware performance counters"
    ],
    "OSS": [
      "orthogonal spectrum sharing",
      "open source software"
    ],
    "MAD": [
      "median absolute difference",
      "median absolute deviations",
      "map attention decision"
    ],
    "POS": [
      "partial optimal slacking",
      "part of speech"
    ],
    "SSD": [
      "solid state disk",
      "single shot detection"
    ],
    "FA": [
      "feature alignment",
      "fractional anisotropy",
      "feedback alignment",
      "failure analysis",
      "firefly algorithm",
      "false alarm",
      "fault attack"
    ],
    "GPA": [
      "gaussian process adaptation",
      "generalized procrustes analysis",
      "graph partition algorithm"
    ],
    "APS": [
      "adaptive patch selection",
      "adaptive patch search",
      "american physical society",
      "augmented path schema"
    ],
    "FEM": [
      "finite element method",
      "finite element methodgm97"
    ],
    "CT": [
      "computed tomography",
      "constraint theory",
      "contributor trust",
      "conditional training",
      "crowd trust",
      "confidential transactions",
      "coordinated turn",
      "class table"
    ],
    "CAD": [
      "coronary artery disease",
      "computer aided design",
      "computer aided diagnosis"
    ],
    "IR": [
      "imbalance ratio",
      "individual rationality",
      "information retrieval",
      "interference range",
      "immediate regret",
      "influence rank",
      "influence ratio",
      "integrates results",
      "incremental relaying",
      "image resolution",
      "inactive region"
    ],
    "SMT": [
      "satisfiability modulo theory",
      "statistical machine translation",
      "semantic mask transfer"
    ],
    "ER": [
      "entity relationship",
      "error rate",
      "erdos - renyi",
      "experience replay",
      "estrogen receptor",
      "entity recognition",
      "encoder rnn"
    ],
    "JCR": [
      "journal citation report",
      "jointly convex representation"
    ],
    "STBM": [
      "stochastic topic block model",
      "stochastic tensor block model"
    ],
    "EC": [
      "evolutionary computation",
      "equivalence class",
      "eigenvector centrality",
      "effective concentration",
      "empty categories",
      "emergent configuration"
    ],
    "UE": [
      "user equilibrium",
      "unreal engine",
      "user equipment"
    ],
    "ODE": [
      "o - d demand estimation",
      "ordinary differential equation"
    ],
    "VI": [
      "vector initialization",
      "variable importance",
      "variational inference",
      "variational information",
      "vegetation indices"
    ],
    "RI": [
      "random indexing",
      "rand index"
    ],
    "DM": [
      "distribution matching",
      "discovery of models",
      "dialog management",
      "directional modulation",
      "data management"
    ],
    "ASE": [
      "amplified spontaneous emission",
      "average scale error"
    ],
    "AIR": [
      "achievable information rates",
      "application instance role"
    ],
    "TL": [
      "tracking logic",
      "transfer learning"
    ],
    "RTS": [
      "request to send",
      "real time strategy"
    ],
    "MAC": [
      "medium access control",
      "multiple access channels",
      "mandatory access control",
      "message authentication code",
      "metropolitan airports commission",
      "multiply accumulate",
      "multiple access control"
    ],
    "DCF": [
      "distributed coordination function",
      "discriminative correlation filter"
    ],
    "GK": [
      "graphlet kernel",
      "greedy knapsack"
    ],
    "DCNN": [
      "deep convolutional neural network",
      "dynamic convolutional neural network"
    ],
    "PSD": [
      "power spectral density",
      "phase shift difference"
    ],
    "CA": [
      "corresponding arcs",
      "current account",
      "contention adaptions",
      "combinatorial auction",
      "cumulative activation",
      "cellular automata",
      "coordinate ascent",
      "classification accuracy",
      "context adaptation",
      "cardiac amyloidosis",
      "contextual attention",
      "conversational analysis",
      "certificate authority",
      "community animator",
      "conditioning augmentation",
      "character - level accuracy",
      "coded aperture"
    ],
    "ICP": [
      "iterative closest point",
      "inductive conformal prediction",
      "iterative cache placement"
    ],
    "MAE": [
      "mean absolute error",
      "maximum absolute error",
      "mean average error"
    ],
    "RL": [
      "reinforcement learning",
      "representation learning",
      "robot learning",
      "relative location",
      "restrained lloyd",
      "resource limitations",
      "robust locomotion"
    ],
    "CRF": [
      "conditional random field",
      "constant rate factor",
      "correlation robust function"
    ],
    "NP": [
      "noun phrase",
      "non - emptiness problem",
      "neural pooling",
      "no peepholes",
      "natural problem",
      "new persian",
      "neural processes"
    ],
    "DSL": [
      "domain - specific language",
      "distributed spectrum ledger"
    ],
    "CV": [
      "cross validation",
      "constant velocity",
      "computer vision",
      "crowd votes"
    ],
    "OT": [
      "oblivious transfer",
      "optimal transport",
      "orthogonal training",
      "optimality theory"
    ],
    "MPC": [
      "multi - party computation",
      "model predictive control",
      "massively parallel computation"
    ],
    "AC": [
      "audio commons",
      "attack criteria",
      "auto - correlation",
      "actor - critic",
      "atrous convolution",
      "access category",
      "autonomic computing",
      "activation clustering",
      "admission control",
      "alternating current",
      "access categories",
      "avoid congestion"
    ],
    "AA": [
      "astronomy and astrophysics",
      "authorship attribution",
      "affine arithmetic",
      "adamic adar"
    ],
    "TI": [
      "temporal interactions",
      "threshold initialization",
      "tone injection",
      "temporal information"
    ],
    "CIA": [
      "confidentiality , integrity , and availability",
      "central intelligence agency"
    ],
    "PR": [
      "preimage resistant",
      "preference ratio",
      "patient record",
      "pilot reuse",
      "precision - recall",
      "perfect reconstruction",
      "passage retrieval",
      "pagerank",
      "perfectly reconstructible"
    ],
    "CR": [
      "collision resistant",
      "cognitive radio",
      "communication region",
      "containment relations",
      "collective rationality",
      "coreference resolution",
      "code rate",
      "carriage returns",
      "contention resolution"
    ],
    "IF": [
      "interference factor",
      "instantaneous frequency",
      "intermediate frequency",
      "isolation forest"
    ],
    "SPA": [
      "simple power analysis",
      "saturation peak analysis",
      "spatial preferential attachment"
    ],
    "SM": [
      "scalar multiplication",
      "spatial modulation",
      "scattering modulation",
      "streaming multiprocessors",
      "synthesis module",
      "stream multiprocessor",
      "speaker model",
      "supplementary material",
      "spectral matching",
      "social media",
      "single service manager",
      "service manager",
      "shared memory",
      "state machine",
      "system model"
    ],
    "PM": [
      "point multiplication",
      "polarization - multiplexed",
      "probabilistic model",
      "physical machines",
      "prediction model"
    ],
    "RPC": [
      "randomized projective coordinate",
      "remote procedure calls"
    ],
    "FPM": [
      "fixed point multiplication",
      "face prediction model"
    ],
    "MPI": [
      "message passing interface",
      "multiple parallel instances"
    ],
    "GA": [
      "global arrays",
      "genetic algorithm",
      "graduated assignment"
    ],
    "LSU": [
      "louisiana state university",
      "load - store unit"
    ],
    "PSC": [
      "pittsburgh supercomputing center",
      "partial set cover",
      "paper sentence classification"
    ],
    "MT": [
      "machine translation",
      "merkle tree"
    ],
    "CS": [
      "computer systems",
      "computer science",
      "clonal selection",
      "connection size",
      "computational science",
      "centralized solution",
      "compressive sensing",
      "core semantics",
      "coordinated scheduling",
      "charging station",
      "constraint solver",
      "conventional sparsity",
      "compressed sensing",
      "critical section",
      "common subset",
      "content store",
      "case - sensitive",
      "consensus score",
      "code - switching",
      "cluster - specific"
    ],
    "LOS": [
      "length of stay",
      "line of sight"
    ],
    "RF": [
      "random forest",
      "radio frequency",
      "regression function",
      "regression forest",
      "register file"
    ],
    "HS": [
      "hourly - similarity",
      "horn and schunck",
      "hierarchical softmax"
    ],
    "VSM": [
      "vector space model",
      "vacationing server model"
    ],
    "CC": [
      "charging current",
      "corpus callosum",
      "collision cone",
      "cross - correlation",
      "creative commons",
      "central cloud",
      "classifier chain",
      "closeness centrality",
      "constant charging",
      "cover complexity",
      "connected caveman",
      "constant current",
      "collaboration coefficient",
      "covert channels",
      "correlation constraints",
      "core connected"
    ],
    "DBN": [
      "deep belief network",
      "dynamic bayesian network",
      "directed belief net"
    ],
    "DR": [
      "dimension reduction",
      "demand response",
      "diagnosis record",
      "detecting repetitions",
      "dispersion reduction",
      "digit reversal",
      "differential rectifier",
      "dimensionality reduction",
      "document retrieval",
      "decoder rnn"
    ],
    "EM": [
      "expectation maximization",
      "exact match",
      "electron microscopy"
    ],
    "FS": [
      "feature selection",
      "frame semantic",
      "fraudulent services",
      "fully sampled",
      "fragment shader"
    ],
    "MA": [
      "moving average",
      "multiple assignment",
      "merlin - arthur",
      "mobile agent"
    ],
    "PSO": [
      "particle swarm optimization",
      "power system operations"
    ],
    "ABC": [
      "artificial bee colony",
      "absorbing boundary condition"
    ],
    "MP": [
      "message passing",
      "matching pursuit",
      "most popular",
      "max pooling",
      "mean precision",
      "mask pyramid"
    ],
    "BM": [
      "bare metal",
      "black males"
    ],
    "VM": [
      "virtual machine",
      "visual module",
      "von mises"
    ],
    "BEA": [
      "building educational applications",
      "bond energy algorithm"
    ],
    "MMD": [
      "maximum mean discrepancy",
      "minimizes marginal distribution"
    ],
    "FC": [
      "fully connected",
      "fusion center",
      "fixed confidence",
      "filter controls",
      "frame content",
      "fashion compatibility",
      "fiscal code"
    ],
    "FP": [
      "function processor",
      "false positive",
      "frequency partitioning",
      "floating point",
      "failure prediction",
      "fixed point"
    ],
    "SDR": [
      "software defined radio",
      "semidefine relaxation",
      "structured domain randomization"
    ],
    "BO": [
      "backoff",
      "bayesian optimisation"
    ],
    "EL": [
      "euler - lagrange",
      "entity linking",
      "edge length",
      "episode length",
      "external links"
    ],
    "LSB": [
      "least squares boosting",
      "least significant bit"
    ],
    "FIM": [
      "fisher information matrix",
      "fragment identifier messaging",
      "fast iterative method"
    ],
    "DF": [
      "direction facilities",
      "dominating frequencies"
    ],
    "ACL": [
      "agent communication language",
      "access control list"
    ],
    "ARC": [
      "australian research council",
      "adaptive - robust control"
    ],
    "SAR": [
      "synthetic aperture radar",
      "socially assistive robots",
      "search and rescue",
      "sensing application recently"
    ],
    "OSI": [
      "open systems interconnection",
      "open source initiative"
    ],
    "RLC": [
      "random linear coding",
      "radio link control"
    ],
    "RS": [
      "running sum",
      "residual splash",
      "rate - selective",
      "relay station",
      "random search",
      "remote sensing",
      "recommender systems",
      "rate splitting",
      "randomly sampled",
      "random split",
      "rate saturation",
      "real satellite"
    ],
    "NN": [
      "neural network",
      "nearest neighbor"
    ],
    "NB": [
      "negative binomial",
      "naive bayes",
      "new brunswick"
    ],
    "HOS": [
      "higher - order spectra",
      "higher order statistics"
    ],
    "SA": [
      "structural accuracy",
      "single architecture",
      "stacked autoencoders",
      "simulated annealing",
      "signal analysis",
      "sensitivity analysis",
      "strongly adaptive",
      "sensing antennas",
      "significance and accuracy",
      "satisfies aass",
      "situational awareness",
      "subspace alignment",
      "steepest ascent",
      "scores anatomical",
      "string analysis"
    ],
    "EI": [
      "expected improvement",
      "epidemic intelligence",
      "event interaction"
    ],
    "MCC": [
      "matthews correlation coefficient",
      "minimum coefficient correlation",
      "mobile cloud computing",
      "mesoscale cellular convection",
      "maximal connected component"
    ],
    "ROC": [
      "receiver operating characteristic",
      "restricted orthogonal constants"
    ],
    "NBC": [
      "naive bayes classifier",
      "non - parametric bayesian classification"
    ],
    "SK": [
      "string kernel",
      "septic shock"
    ],
    "MTL": [
      "medial temporal lobe",
      "multi - task learning"
    ],
    "IL": [
      "imitation learning",
      "intermediate level"
    ],
    "DMP": [
      "dynamic movement primitives",
      "digital motion processor"
    ],
    "GCP": [
      "graph compression problem",
      "grid connection point"
    ],
    "IP": [
      "intellectual property",
      "internet protocol",
      "inductive programming",
      "inverse proportion",
      "intercept probability",
      "image preprocessing",
      "integer programming"
    ],
    "TLS": [
      "transport layer security",
      "terrestrial laser scanning"
    ],
    "PAD": [
      "probe attempt detector",
      "presentation attack detection"
    ],
    "ASM": [
      "active shape model",
      "alphabet set multiplier"
    ],
    "DMD": [
      "dynamic mirror descent",
      "digital micro - mirror device",
      "deficient mapping dissolution"
    ],
    "EMA": [
      "exponential moving average",
      "ecological momentary assessment"
    ],
    "MAPE": [
      "mean absolute percentage error",
      "mean average percent error"
    ],
    "MAP": [
      "maximum a posteriori",
      "mean average precision"
    ],
    "DN": [
      "distinguished name",
      "destination node"
    ],
    "PCC": [
      "pre - activation convolutional cell(the",
      "pearson correlation coefficient"
    ],
    "AL": [
      "adversarial loss",
      "active learning"
    ],
    "US": [
      "ultrasound",
      "united states",
      "uncertainty sampling"
    ],
    "MR": [
      "magnetic resonance",
      "minimum read",
      "majority rule",
      "model risk",
      "middle resolution",
      "mean recall",
      "machine reading",
      "meaning representation",
      "morphological richness",
      "mixed reality"
    ],
    "HR": [
      "high - resolution",
      "heart rate"
    ],
    "IS": [
      "inception score",
      "importance sampling",
      "information systems"
    ],
    "LDP": [
      "large deviation principle",
      "low degeneracy partition",
      "local differential privacy"
    ],
    "ACE": [
      "average causal effect",
      "advanced combined encoder",
      "average coverage error"
    ],
    "OPS": [
      "orthogonal pilot sequences",
      "one posterior sample"
    ],
    "MDS": [
      "maximum distance separable",
      "minimum dominating set",
      "multi - dimensional scaling"
    ],
    "IPS": [
      "intrusion prevention system",
      "inverse propensity scaling",
      "interactive proof systems"
    ],
    "BMS": [
      "building management system",
      "battery management system"
    ],
    "PP": [
      "prepositional phrase",
      "point process",
      "pairwise product",
      "pairwise perturbation",
      "privacy preferences",
      "present and predominant"
    ],
    "PF": [
      "particle filter",
      "pareto - fair",
      "propagation fusion",
      "power flow",
      "poloidal field"
    ],
    "NF": [
      "naive fusion",
      "noise figure",
      "new foundations"
    ],
    "TAM": [
      "technology acceptance model",
      "transparent attention model"
    ],
    "DFT": [
      "density functional theory",
      "discrete fourier transformation",
      "disk failure tolerant",
      "design - for - test"
    ],
    "CKD": [
      "conditional kernel density",
      "child key derivation",
      "chronic kidney disease"
    ],
    "AR": [
      "auto - regression",
      "average recall",
      "anaphora resolution",
      "augmented reality",
      "accumulated reward"
    ],
    "CSPs": [
      "cloud service providers",
      "constraint satisfaction problems"
    ],
    "CAP": [
      "consistency availability partition",
      "cumulative accuracy profit",
      "carrier - less amplitude and phase"
    ],
    "DSM": [
      "data store module",
      "data stream manager",
      "demand side management",
      "distributional semantic model",
      "digital surface model"
    ],
    "CAS": [
      "content addressed storage",
      "computer algebra systems",
      "consensus attention sum"
    ],
    "PD": [
      "progressive disease",
      "prisoner 's dilemma",
      "pu - primary destination",
      "positive definite",
      "parkinson 's disease",
      "pixel discussion"
    ],
    "PPMI": [
      "parkinson 's progression markers initiative",
      "positive pointwise mutual information"
    ],
    "EHRs": [
      "electronic health records",
      "energy harvesting receivers"
    ],
    "LCP": [
      "linear complementarity problem",
      "locally compact polish",
      "longest common prefix",
      "linearly compressed page"
    ],
    "SD": [
      "strong dominance",
      "secure digital",
      "standard deviation",
      "strategic dependency",
      "soft decision",
      "symbolic differentiation",
      "sphere decoding",
      "selection diversity",
      "stochastically dominate",
      "structural diagram"
    ],
    "GVF": [
      "generalized value function",
      "gradient vector flow"
    ],
    "ASA": [
      "adaptive segmentation algorithm",
      "accessible surface area"
    ],
    "GMM": [
      "gaussian mixture model",
      "group marching method"
    ],
    "MD": [
      "molecular dynamics",
      "morphological disambiguation",
      "mixed decoding",
      "model distillation",
      "memoryless deterministic",
      "mean diffusivity",
      "massa de dados",
      "multiple description",
      "missed detection"
    ],
    "LP": [
      "linear programming",
      "label powerset",
      "label propagation"
    ],
    "CPM": [
      "critical path method",
      "competition performance metric",
      "completely positive maps",
      "clique percolation method",
      "continuous profile model",
      "cost per mille"
    ],
    "HD": [
      "hausdorff distance",
      "high definition",
      "hard decision",
      "harmonic distortion",
      "huntington 's disease"
    ],
    "LD": [
      "levenshtein distance",
      "line difference",
      "loads data",
      "large deviation",
      "link density"
    ],
    "ST": [
      "stomach",
      "split - turnip",
      "sleep telemetry",
      "semantic tagging",
      "single trails",
      "smart thermostat",
      "steiner tree"
    ],
    "RK": [
      "right kidney",
      "root key"
    ],
    "RDM": [
      "russian dolls model",
      "representational dissimilarity matrix"
    ],
    "NEB": [
      "nudged elastic band",
      "next event backtracking"
    ],
    "CF": [
      "collaborative filtering",
      "crest factor",
      "code - mixed factor",
      "complexity factor",
      "correlation filter"
    ],
    "CTR": [
      "click through rates",
      "collaborative topic regression",
      "character transfer rate"
    ],
    "MF": [
      "matrix factorization",
      "model fair",
      "membership function",
      "model - free"
    ],
    "ET": [
      "energy transmitters",
      "evidence theory",
      "enhancing tumor",
      "elastic transformations",
      "emission tomography"
    ],
    "ANN": [
      "approximate nearest neighbor",
      "artificial neural network"
    ],
    "AI": [
      "artificial intelligence",
      "article influence"
    ],
    "DPI": [
      "deep packet inspection",
      "data processing inequality"
    ],
    "LR": [
      "logistic regression",
      "learning rate",
      "linear regression",
      "low resolution",
      "lp relaxation",
      "low rank"
    ],
    "TPR": [
      "true positive rate",
      "tensor product representation"
    ],
    "RR": [
      "round robin",
      "recurrent refinement",
      "relevance rate",
      "relative ranking",
      "reverse reachable"
    ],
    "LM": [
      "language model",
      "logarithmically scaled magnitude",
      "lagrange multiplier method",
      "levenberg macquardt"
    ],
    "OS": [
      "overlap success",
      "output stride",
      "orientation score",
      "operating system"
    ],
    "SRC": [
      "sdn ran controller",
      "spearsman 's rank correlation",
      "sparse representation classification"
    ],
    "LTE": [
      "long term evolution",
      "language transmission engine"
    ],
    "HN": [
      "heterogeneous network",
      "hierarchical network"
    ],
    "PI": [
      "prediction intervals",
      "provider independent",
      "power iteration",
      "purchase intention"
    ],
    "PNN": [
      "probabilistic neural network",
      "product - based neural network",
      "progressive neural networks"
    ],
    "RDF": [
      "resource description framework",
      "rate distortion function",
      "random decision forests"
    ],
    "GDP": [
      "gross domestic product",
      "generalized differential privacy",
      "good distribution practice"
    ],
    "SO": [
      "smart object",
      "stack overflow",
      "surrogate outcomes"
    ],
    "SMP": [
      "security management provider",
      "symmetric multi processor",
      "stable marriage problem"
    ],
    "DC": [
      "distributed control",
      "dublin core",
      "direct current",
      "dual connectivity",
      "disorder constraints",
      "disconnected components",
      "direct click",
      "descriptive complexity",
      "data consistency",
      "datacenter",
      "dice coefficient",
      "deep convolutional",
      "deficit counter",
      "dynamic cluster"
    ],
    "ADP": [
      "approximate dynamic programming",
      "absolute derivative privacy"
    ],
    "ES": [
      "energy storage",
      "end systolic",
      "evolutionary strategies",
      "encrypted sharing",
      "event synchronization",
      "enterprise storage",
      "entropy search",
      "elevation angle spread",
      "exhaustive search",
      "external search",
      "embedding weight sharing"
    ],
    "TR": [
      "temporal resolution",
      "tone reservation"
    ],
    "AOD": [
      "average outage duration",
      "angle opening distance"
    ],
    "AM": [
      "arithmetic mean",
      "activation maximization",
      "alternating minimization"
    ],
    "QP": [
      "quadratic programming",
      "quantum pareto",
      "quantisation parameter"
    ],
    "TCP": [
      "test case prioritization",
      "top concept 's popularity",
      "transductive conformal prediction",
      "transmission control protocol"
    ],
    "SDD": [
      "stanford drone dataset",
      "standard desktop display"
    ],
    "VAT": [
      "virtual adversarial training",
      "visceral adipose tissue"
    ],
    "GP": [
      "gaussian process",
      "geometric programming"
    ],
    "SAD": [
      "spectral angle distance",
      "speech activity detection"
    ],
    "OI": [
      "original images",
      "operational intensity"
    ],
    "SR": [
      "stacked refinement",
      "secrecy rate",
      "segment representation",
      "spatial resolution",
      "success rate",
      "super resolution",
      "speech recognition",
      "small resolution",
      "strategic rationale",
      "systematic review"
    ],
    "SSA": [
      "space situational awareness",
      "static single assignment"
    ],
    "SPL": [
      "sound pressure level",
      "shortest path length",
      "standard plane location"
    ],
    "TP": [
      "true positives",
      "temporal pooler"
    ],
    "FN": [
      "false negatives",
      "focusing network"
    ],
    "TN": [
      "true negative",
      "total noise"
    ],
    "AP": [
      "average precision",
      "access point",
      "asymptotic preserving",
      "associated press",
      "acute pancreatitis",
      "access part",
      "affinity propagation"
    ],
    "DE": [
      "dimension estimation",
      "differential evolution",
      "dataexplorer",
      "deterministic equivalent",
      "data efficiency"
    ],
    "PAM": [
      "partitioning around medoid",
      "passive acoustic monitoring",
      "pulse amplitude modulation"
    ],
    "MGM": [
      "markov geographic model",
      "manifold geometry matching"
    ],
    "ASR": [
      "automatic speech recognition",
      "average sum rate"
    ],
    "DL": [
      "description length",
      "deep learning",
      "dice loss",
      "description logics",
      "downlink",
      "distributed ledger",
      "depth loss",
      "dogleg"
    ],
    "CFG": [
      "context free grammar",
      "control flow graph"
    ],
    "CP": [
      "constraint programming",
      "cyclic prefic",
      "clustered placement",
      "central processor",
      "canonical polyadic",
      "completely positive",
      "constraint problem",
      "control program",
      "candecomp / parafac",
      "conformal prediction",
      "core periphery"
    ],
    "LS": [
      "local search",
      "least squares",
      "logarithmically spaced",
      "linear systemswe",
      "location service"
    ],
    "DP": [
      "dynamic programming",
      "distance precision",
      "declustered placement",
      "dirichlet process",
      "drift - plus penalty",
      "dropped pronoun",
      "direct proportion",
      "differential privacy",
      "disjunctive programming",
      "dronemap planner"
    ],
    "CLP": [
      "convergence layer protocol",
      "coin - or linear program solver"
    ],
    "SAC": [
      "special airworthiness certificate",
      "soft actor critic"
    ],
    "HAP": [
      "high altitude platform",
      "hybrid access point"
    ],
    "MSC": [
      "multi - layer same - resolution compressed",
      "mobile switching center"
    ],
    "CRM": [
      "channel reliability measurement",
      "counterfactual risk minimization"
    ],
    "LDOF": [
      "large displacement optical flow",
      "local distance - based outlier factor"
    ],
    "BA": [
      "black and anandan",
      "binary agreement",
      "barabasi albert",
      "bundle adjustment",
      "balanced accuracy",
      "bee algorithm"
    ],
    "MS": [
      "modelling simulation",
      "multiple sclerosis",
      "mean shift",
      "missed speech",
      "main - sequence",
      "mid stance",
      "mobile station",
      "medical sentiment"
    ],
    "SDP": [
      "shortest dependency path",
      "semi - definite programming",
      "stable dependencies principle"
    ],
    "LMF": [
      "low - rank multimodal fusion",
      "lower membership function"
    ],
    "GAP": [
      "global average pooling",
      "generative adversarial perturbations",
      "generalized assignment problem",
      "global average precision"
    ],
    "BPM": [
      "beat per minute",
      "business process modelling"
    ],
    "BD": [
      "bias disparities",
      "bjontegaard delta",
      "block diagonalization",
      "benders decomposition"
    ],
    "QA": [
      "question answering",
      "quantum annealing"
    ],
    "CCC": [
      "concordance correlation coefficient",
      "congruence coefficient correlation"
    ],
    "RC": [
      "rich club",
      "radon consistency",
      "reading comprehension",
      "relation classification",
      "remote control",
      "resource control",
      "recurrent convolution",
      "radio control",
      "rate constrained",
      "red clump",
      "reservoir computing"
    ],
    "CI": [
      "current iteration",
      "confidence intervals",
      "constructive interference",
      "class imbalance",
      "conditional independence",
      "current instruction",
      "cochlear implant",
      "continuous integration",
      "computational intelligence"
    ],
    "SOA": [
      "stimulus onset asynchrony",
      "service oriented architecture"
    ],
    "MAT": [
      "medication assisted treatment",
      "motionless analysis of traffic",
      "multi - fingered adaptive tactile grasping"
    ],
    "MSD": [
      "million song dataset",
      "modified list sphere decoding",
      "most significant digit"
    ],
    "GBM": [
      "geometric brownian motion",
      "gradient boosting machine"
    ],
    "AS": [
      "autonomous system",
      "angular spread",
      "adaptive softmax",
      "ancillary service",
      "azimuth angle spread",
      "attention sum",
      "antenna spacing"
    ],
    "TD": [
      "total difficulty",
      "time - discrete",
      "technical debt",
      "temporal difference",
      "temporal dimension",
      "training data",
      "target dependent",
      "top - down",
      "time - domain"
    ],
    "CPI": [
      "consumer price index",
      "conditional predictive impact"
    ],
    "RN": [
      "relational neighbors",
      "radical nephrectomy",
      "relay nodes",
      "random noise",
      "radial normalization"
    ],
    "SN": [
      "secondary node",
      "source node",
      "spectral normalization"
    ],
    "RV": [
      "random vaccination",
      "right ventricle",
      "random voting",
      "random variable",
      "resilience vector",
      "range view"
    ],
    "AV": [
      "acquaintance vaccination",
      "antivirus",
      "autonomous vehicle"
    ],
    "ACR": [
      "air change rates",
      "absolute category rating"
    ],
    "CN": [
      "common neighbours",
      "clustered networks",
      "core network",
      "cognitively normal",
      "common noun"
    ],
    "CFA": [
      "color filter arrays",
      "constriction factor approach",
      "counterfactual future advantage"
    ],
    "DAS": [
      "data availability statement",
      "disclosure avoidance system"
    ],
    "HF": [
      "hybrid fusion",
      "high frequency"
    ],
    "MC": [
      "mean - centering",
      "myocardium",
      "monte carlo",
      "multi connectivity",
      "marginal contribution",
      "markov chain",
      "mutual cover",
      "matrix converter"
    ],
    "ATE": [
      "absolute trajectory error",
      "average translation error"
    ],
    "RPE": [
      "relative pose error",
      "retinal pigment epithelium"
    ],
    "CMS": [
      "codeword mixture sampling",
      "counting monadic second"
    ],
    "DVS": [
      "dynamic vision sensor",
      "dynamic voltage scaling"
    ],
    "ED": [
      "economic dispatch",
      "emergency department",
      "embedded deformation",
      "euclidean distance",
      "energy detection"
    ],
    "APP": [
      "australian privacy principles",
      "a posteriori probability"
    ],
    "CM": [
      "canalizing map",
      "centroid methods",
      "confusion matrix",
      "continental margin",
      "corporate messaging",
      "choir mix",
      "coded modulation"
    ],
    "SC": [
      "sleep cassette",
      "sum capacity",
      "steering control",
      "smallest class",
      "successive cancellation",
      "score contextualisation",
      "self cover",
      "subset compared",
      "spectral clustering",
      "smart contract",
      "self consistency",
      "selection combining",
      "sum capacities",
      "symmetry condition",
      "single connectivity",
      "special case",
      "spatial crowdsourcing",
      "strongly connected"
    ],
    "SW": [
      "similarity weight",
      "sliding window",
      "small - world"
    ],
    "RCNN": [
      "recurrent convolutional neural network",
      "region based convolutional neural network"
    ],
    "ESE": [
      "entity set expansion",
      "extract similar entities"
    ],
    "GEM": [
      "gradient episodic memory",
      "grid entropy measurement"
    ],
    "OLS": [
      "orthogonal least square",
      "ordinary least square"
    ],
    "OSA": [
      "opportunistic spectrum access",
      "obstructive sleep apnoea"
    ],
    "SF": [
      "satisfaction function",
      "sequential fixing",
      "scale free",
      "structure fusion",
      "small faces",
      "separable footprints",
      "state - feedback"
    ],
    "CH": [
      "cluster head",
      "constraint handling"
    ],
    "BP": [
      "belief propagation",
      "bin packing",
      "basis pursuit",
      "backprop",
      "back propagation",
      "backdoor poisoning",
      "bundle protocol",
      "best performing"
    ],
    "LC": [
      "latent class",
      "local conditioning",
      "line card",
      "least confidence",
      "largest class",
      "land cover",
      "latent clustering",
      "lyrics comprehension"
    ],
    "FTE": [
      "foveal tilt effects",
      "full time employment"
    ],
    "HT": [
      "hough transform",
      "hoeffding tree"
    ],
    "SER": [
      "symbol error rate",
      "speaker error rate",
      "speech emotion recognition"
    ],
    "BS": [
      "base station",
      "beam search",
      "brier score",
      "batch size",
      "standard beam search",
      "bayesian sets",
      "bidirectional similarity"
    ],
    "BT": [
      "best target",
      "back translation",
      "bernoulli trial"
    ],
    "RB": [
      "random beamforming",
      "resource blocks",
      "rank - based",
      "reduced basis",
      "rosi braidotti"
    ],
    "UD": [
      "universal dependencies",
      "unified distillation"
    ],
    "GN": [
      "gaussian noise",
      "grid name",
      "gauss - newton"
    ],
    "GCNN": [
      "graph convolutional neural network",
      "geodesic convolution neural network"
    ],
    "GCN": [
      "generalised convolutional neural network",
      "graph convolution networks",
      "global convolution networks"
    ],
    "HAN": [
      "hierarchical attention network",
      "heterogeneous attributed network"
    ],
    "HMP": [
      "hierarchical matching pursuit",
      "hypermutations with mutation potential"
    ],
    "BPE": [
      "byte pair encoding",
      "backward partial execution"
    ],
    "ASD": [
      "autism spectrum disorders",
      "average surface distance"
    ],
    "SWD": [
      "sliced wasserstein distance",
      "semantic web deployment"
    ],
    "BAM": [
      "behance artistic media",
      "best alignment metric",
      "bandwidth allocation model"
    ],
    "SSR": [
      "spatial skeleton realignment",
      "sparse signal recovery",
      "spectral super - resolution"
    ],
    "EB": [
      "energy buffer",
      "energy beam"
    ],
    "SI": [
      "satellite imagery",
      "semantic inpainting"
    ],
    "AN": [
      "artificial noise",
      "attention network"
    ],
    "ESC": [
      "environment sound classification",
      "ergodic sum capacity"
    ],
    "TSP": [
      "traveling salesman problem",
      "triad significance profile"
    ],
    "LPP": [
      "locality preserving projections",
      "load planning problem"
    ],
    "ITS": [
      "intelligent transportation system",
      "interrupted time series",
      "intelligent tutoring systems"
    ],
    "CST": [
      "corticospinal tract",
      "china standard time"
    ],
    "CMI": [
      "conditional mutual information",
      "code - mixed index"
    ],
    "SCA": [
      "successive convex approximation",
      "scatter component analysis",
      "smart cut algorithm"
    ],
    "ISP": [
      "internet service providers",
      "image signal processor"
    ],
    "BNC": [
      "british national corpus",
      "brown news corpus"
    ],
    "MACS": [
      "mean average conceptual similarity",
      "minimum average conceptual similarity"
    ],
    "ADA": [
      "american diabetes association 's",
      "adaptive data augmentation"
    ],
    "DS": [
      "delay spread",
      "direct sharing",
      "data structure",
      "data sharing",
      "differentiated softmax",
      "dempster - shafer",
      "detection scores"
    ],
    "MSA": [
      "modern standard arabic",
      "multilevel splitting algorithm",
      "multiple sequence alignment"
    ],
    "DES": [
      "dual energy subtraction",
      "defence equipment support"
    ],
    "SFC": [
      "superposition of functional contours",
      "service function chaining"
    ],
    "PLP": [
      "perceptual linear prediction",
      "poisson line process"
    ],
    "FPR": [
      "false positive rate",
      "fuzzy preference relation"
    ],
    "BDT": [
      "boosted decision trees",
      "bi - directional domain translation"
    ],
    "PAP": [
      "process arrival pattern",
      "policy administration point"
    ],
    "RM": [
      "roofline model",
      "robot middleware",
      "representation mixing",
      "resource management"
    ],
    "EAD": [
      "encoded archival description",
      "exponential absolute distance"
    ],
    "DCP": [
      "deep context prediction",
      "darwin correspondence project"
    ],
    "VO": [
      "velocity obstacle",
      "visual odometry"
    ],
    "ECC": [
      "error correcting code",
      "elliptic curve cryptography"
    ],
    "ASN": [
      "autonomous system number",
      "average sample number"
    ],
    "LSA": [
      "latent semantic analysis",
      "licensed shared access"
    ],
    "SMC": [
      "sequential monte carlo",
      "sliding mode control",
      "statistical model checking",
      "secure multiparty computation"
    ],
    "EO": [
      "eyes open",
      "earth observation"
    ],
    "EDA": [
      "evolutionary distribution algorithm",
      "exploratory data analysis"
    ],
    "DRL": [
      "deep reinforcement learning",
      "distributional reinforcement learning"
    ],
    "PG": [
      "policy gradient",
      "policy generator",
      "property graph"
    ],
    "ROM": [
      "range of motion",
      "reduced - order models"
    ],
    "ICC": [
      "intraclass correlation coefficient",
      "implicit computational complexity"
    ],
    "MBR": [
      "minimum bandwidth regenerating",
      "minimum bounding rectangle"
    ],
    "DT": [
      "decision tree",
      "delivery teams"
    ],
    "RLS": [
      "recursive least squares",
      "regularized least squares",
      "random local search"
    ],
    "SP": [
      "strictly piecewise",
      "streaming processors",
      "set partitioning",
      "subspace pursuit",
      "stream processor",
      "shilling profiles",
      "semantic parsing",
      "shortest path",
      "spatial pooler",
      "standards poors",
      "sao paulo",
      "set point",
      "splitting problem"
    ],
    "SL": [
      "strictly local",
      "separation logic",
      "supervised learning"
    ],
    "CLS": [
      "constrained least squares",
      "complementary learning systems"
    ],
    "ARA": [
      "adversarial risk analysis",
      "accumulate repeat accumulate"
    ],
    "POI": [
      "points of interest",
      "projection of interest"
    ],
    "RSS": [
      "received signal strength",
      "radio signal strength",
      "random subcarrier selection"
    ],
    "CSD": [
      "constrained spherical deconvolution",
      "critical sensor density",
      "contextual sentence decomposition"
    ],
    "PN": [
      "pixel - wise normalization",
      "partial nephrectomy"
    ],
    "PA": [
      "provider aggregatable",
      "philadelphia",
      "physical access",
      "peano 's arithmetics",
      "parallel attention",
      "preferential attachment",
      "power allocation",
      "presburger arithmetic"
    ],
    "FD": [
      "fast dormancy",
      "finite differences",
      "fractal dimension",
      "fully - digital"
    ],
    "IC": [
      "initial contact",
      "integrated circuit",
      "independent cascading"
    ],
    "SPM": [
      "statistical parameter mapping",
      "saliency prediction model",
      "spatial pyramid matching"
    ],
    "EMD": [
      "earth mover 's distance",
      "excessive mapping dissolution"
    ],
    "CRC": [
      "cyclic redundancy check",
      "collaborative representation classification"
    ],
    "ADN": [
      "artifact disentanglement network",
      "activity driven networks"
    ],
    "TU": [
      "threshold updation",
      "translation unit"
    ],
    "OEC": [
      "oxford english corpus",
      "online elliptical clustering"
    ],
    "BSM": [
      "basic skill module",
      "basic safety messages"
    ],
    "BNN": [
      "bayesian neural networks",
      "binary neural networks"
    ],
    "GVR": [
      "gradient variance regularizer",
      "global visual representations"
    ],
    "SCCs": [
      "strongly connected components",
      "static camera clusters"
    ],
    "RT": [
      "radiation therapy",
      "retweets",
      "reparameterization trick",
      "response time",
      "ruthes",
      "random target",
      "region template"
    ],
    "RW": [
      "reaction wheels",
      "random walk",
      "rolling window"
    ],
    "LV": [
      "left ventricle",
      "las vegas",
      "large volumetric"
    ],
    "RG": [
      "renormalization group",
      "riemmanian geometry",
      "real graphs",
      "reber grammar"
    ],
    "AT": [
      "asteroidal triple",
      "adversarial training",
      "adaptive threshold"
    ],
    "CCR": [
      "correct classification ratio",
      "cross - document coreference resolution",
      "correct correction rate"
    ],
    "GMP": [
      "gain minus pain",
      "global max pooling"
    ],
    "CBT": [
      "children 's book test",
      "consensus - before - talk"
    ],
    "DAR": [
      "dynamic assignment ratio",
      "defence application register"
    ],
    "TSA": [
      "temporary scope association",
      "taobao search advertising",
      "temporal semantic analysis"
    ],
    "MI": [
      "myocardial infarction",
      "mutual information",
      "motor imagery",
      "mathematical induction"
    ],
    "PVC": [
      "premature ventricular contraction",
      "passive voltage contrast"
    ],
    "WT": [
      "wavelet transform",
      "wild type",
      "whole tumor",
      "william thackeray"
    ],
    "AAL": [
      "automated anatomical labeling",
      "ambient assisted living"
    ],
    "DA": [
      "denoised auto - encoder",
      "data assimilation",
      "deterministic annealing",
      "domain adaptation",
      "data augmentation",
      "direct assessment",
      "dialogue acts",
      "distribution alignment"
    ],
    "MIR": [
      "music information retrieval",
      "music instrument recognition",
      "music information research"
    ],
    "DCT": [
      "document creation time",
      "download completion time",
      "discrete cosine transformation"
    ],
    "PLS": [
      "partial least square",
      "physical layer security",
      "progressive lesion segmentation"
    ],
    "PC": [
      "program counter",
      "point cloud",
      "program committee",
      "principal component"
    ],
    "CNS": [
      "central nervous system",
      "copenhagen networks study"
    ],
    "AD": [
      "alzheimer 's disease",
      "automatic differentiation",
      "audit department",
      "anomaly detection",
      "auction distribution",
      "artificially - degraded",
      "axial diffusivity"
    ],
    "PL": [
      "path loss",
      "polarity loss",
      "programming language",
      "parallel lexicon",
      "photoluminescence"
    ],
    "CMC": [
      "cumulative matching characteristic",
      "crude monte carlo"
    ],
    "CER": [
      "character error rate",
      "classification error rate",
      "clustering error rate"
    ],
    "FE": [
      "fire emblem",
      "finite element",
      "feature extraction"
    ],
    "NC": [
      "network coding",
      "normalized correlation",
      "north carolina",
      "new classes",
      "noise clinic",
      "network centre",
      "next corollary",
      "node classification",
      "news commentary"
    ],
    "CTC": [
      "connectionist temporal classification",
      "common test conditions"
    ],
    "ZF": [
      "zero forcing",
      "zero - filled"
    ],
    "SE": [
      "spectral efficiency",
      "situation entity",
      "smarteda",
      "sequential exploring",
      "software engineering",
      "strong elimination",
      "signed error",
      "speech enhancement",
      "signal enhancement",
      "squared exponential",
      "selective eraser",
      "small enough",
      "systems engineering"
    ],
    "DAC": [
      "disk array controller",
      "distributed admission control"
    ],
    "GRD": [
      "group rotate declustering",
      "ground range detected"
    ],
    "ALS": [
      "aerial laser scanner",
      "alternating least squares"
    ],
    "CE": [
      "cross entropy",
      "contrastive estimation",
      "context entities",
      "category embeddings",
      "context encoder",
      "crossing event"
    ],
    "ICA": [
      "imperialist competitive algorithm",
      "independent component analysis"
    ],
    "WS": [
      "weight superiority",
      "word shape",
      "word sequence",
      "write skew"
    ],
    "SCM": [
      "semantic correlation maximization",
      "spatial compositional model",
      "scanning capacitance microscopy"
    ],
    "BF": [
      "blind forwarding",
      "basic feature",
      "bayes factor",
      "bilateral filtering",
      "black females",
      "binary function",
      "brute force search",
      "bayesian filtering"
    ],
    "PAF": [
      "provider - aware forwarding",
      "plenacoustic function"
    ],
    "GC": [
      "garbage collector",
      "graph cuts",
      "graph convolution"
    ],
    "SIS": [
      "sequential importance sampling",
      "social identification system"
    ],
    "VC": [
      "voice conversion",
      "virtual classifier"
    ],
    "PS": [
      "prediction shift",
      "parameter server",
      "personal storage",
      "probabilistic serial",
      "power splitting",
      "projective simulation",
      "processor sharing"
    ],
    "UAS": [
      "unlabeled attachment score",
      "unmanned aircraft systems"
    ],
    "BI": [
      "business intelligence",
      "bayesian inference",
      "bilinear interpolation"
    ],
    "NE": [
      "nash equilibrium",
      "named entity",
      "nested experiments"
    ],
    "FM": [
      "factorization machines",
      "formal methods",
      "feature matching",
      "flash memory",
      "forward models",
      "fowlkes mallows index",
      "feature map",
      "f1-measure",
      "frequency modulation",
      "finite mixture",
      "fuzzy measure"
    ],
    "MRE": [
      "mean relative error",
      "median recovery error"
    ],
    "BDI": [
      "belief , desire , intention",
      "beck 's depression inventory"
    ],
    "TE": [
      "transformation encoder",
      "taylor expansion",
      "transformation error",
      "temporal expressions"
    ],
    "APT": [
      "anytime parameter - free thresholding",
      "advanced persistent threat"
    ],
    "NR": [
      "new radio",
      "nuclear receptor"
    ],
    "ART": [
      "adaptive radix tree",
      "adaptive resonance theory"
    ],
    "GM": [
      "genetically modified",
      "gradient magnitude",
      "graph matching",
      "generator matrix"
    ],
    "LB": [
      "lower bound",
      "lovasz bregman"
    ],
    "IPC": [
      "instructions per cycle",
      "individual pitch control",
      "international patent classification"
    ],
    "LT": [
      "lomonosov 's turnip",
      "likelihood test",
      "linear threshold",
      "luby transform",
      "label transfer"
    ],
    "DOM": [
      "document object model",
      "degrees of measurement"
    ],
    "ESR": [
      "equivalent series resistances",
      "extended support release"
    ],
    "PCM": [
      "peak current mode",
      "phase change memory",
      "permanent customer model"
    ],
    "IB": [
      "imaginary batches",
      "information bottleneck",
      "immersed boundary"
    ],
    "FL": [
      "flatten layer",
      "federated learning",
      "fixated locations"
    ],
    "GD": [
      "group delay",
      "gradient descent"
    ],
    "BPD": [
      "baseband phase difference",
      "basis pursuit denoising"
    ],
    "SCP": [
      "squared cosine proximity",
      "simultaneous closeness - performance"
    ],
    "ECN": [
      "explicit congestion notification",
      "edge computing node"
    ],
    "GRL": [
      "gradient reversal layer",
      "goal - oriented requirement language"
    ],
    "GS": [
      "gold standard",
      "group sweep",
      "gauss seidel",
      "geometric sequence",
      "genetic search",
      "google scholar 's"
    ],
    "IM": [
      "instant messaging",
      "identity mapping",
      "intensity modulation",
      "influence maps",
      "interference margin",
      "index modulation"
    ],
    "UI": [
      "user interface",
      "uniform indicator"
    ],
    "PRR": [
      "packet reception rate",
      "pre - reduced ring"
    ],
    "DPs": [
      "dropped pronouns",
      "dependency pairs"
    ],
    "NLM": [
      "neural logic machines",
      "neural language modelling"
    ],
    "ACC": [
      "anomaly correlation coefficient",
      "accuracy",
      "adaptive cruise control"
    ],
    "CG": [
      "conjugate gradient",
      "correspondence grouping",
      "context - guided attention",
      "contour generator",
      "context gating",
      "chemical graph",
      "candidate generation"
    ],
    "DG": [
      "distributed generation",
      "dynamic graph",
      "discontinuous galerkin",
      "domain generalization"
    ],
    "SNP": [
      "single nucleotide polymorphisms",
      "state neighborhood probability"
    ],
    "MDR": [
      "multifactor dimensionality reduction",
      "message dropping rate"
    ],
    "CL": [
      "cumulative link",
      "coupling layers",
      "curriculum learning",
      "continual learning",
      "classical logic"
    ],
    "DIC": [
      "directed interval class",
      "dynamic induction control",
      "deviance information criterion"
    ],
    "AEC": [
      "accepting end component",
      "automatic exposure control"
    ],
    "SGNS": [
      "syntactic symmetric pattern",
      "skip - gram with negative sampling"
    ],
    "OCC": [
      "one class classifier",
      "output constrained covariance",
      "open circuit condition"
    ],
    "AOT": [
      "adaptive on time",
      "adaptively optimised threshold"
    ],
    "RA": [
      "random access",
      "ring allreduce",
      "resource allocation",
      "random attack",
      "remote attestation",
      "right atrium"
    ],
    "PMF": [
      "probabilistic matrix factorization",
      "probability mass function"
    ],
    "DOE": [
      "department of energy",
      "design of experiment",
      "diffractive optical element"
    ],
    "RP": [
      "replies",
      "reciprocal pagerank",
      "reference point",
      "random priority",
      "replacement paths"
    ],
    "CSP": [
      "constraint satisfaction problem",
      "content security policy",
      "cloud service providers",
      "coverage sampling problem",
      "common spatial patterns"
    ],
    "PDR": [
      "pedestrian dead reckoning",
      "packet delivery ratio"
    ],
    "TTI": [
      "transmission time interval",
      "time transmit interval"
    ],
    "MM": [
      "mathematical model",
      "maximum mark"
    ],
    "PE": [
      "processing element",
      "portable executable"
    ],
    "FFT": [
      "fast fourier transformation",
      "feature finding team"
    ],
    "TDS": [
      "taint dependency sequences",
      "training data set"
    ],
    "GT": [
      "group testing",
      "generic tool",
      "ground truth",
      "graph traversal",
      "google translate"
    ],
    "CSS": [
      "compressive spectrum sensing",
      "chirp spread spectrum",
      "cooperative spectrum sensing",
      "cascade style sheet"
    ],
    "IV": [
      "initialization vector",
      "intersection viewer"
    ],
    "OF": [
      "optical flow",
      "objective function"
    ],
    "VFC": [
      "vehicular fog computing",
      "vector filed consensus"
    ],
    "TBS": [
      "transport block sizes",
      "terrestrial base station"
    ],
    "SEP": [
      "separator",
      "symbol error probability"
    ],
    "BR": [
      "boundary refinement",
      "binary relevance",
      "bug reports",
      "belief revision",
      "best response",
      "bone region"
    ],
    "RWA": [
      "random walker algorithm",
      "right wing authoritarianism",
      "recurrent weighted average"
    ],
    "DCI": [
      "downlink control information",
      "downlink control indicator"
    ],
    "RE": [
      "resource elements",
      "relation extraction",
      "renewable energy",
      "requirements elicitation",
      "referring expression"
    ],
    "PDF": [
      "probability density function",
      "portable document format",
      "primary distribution format"
    ],
    "PAT": [
      "perform adversarial training",
      "process arrival time"
    ],
    "SIC": [
      "successive interference cancellation",
      "static induction control",
      "self interference cancellation"
    ],
    "DFA": [
      "direct feedback alignment",
      "deterministic finite automaton"
    ],
    "IEC": [
      "information embedding cost",
      "international electrotechnical commission"
    ],
    "IAN": [
      "introspective adversarial network",
      "interference as noise"
    ],
    "WN": [
      "weak normalization",
      "weight normalization"
    ],
    "TTP": [
      "trusted third party",
      "total transmit power"
    ],
    "SSM": [
      "state space model",
      "statistical shape modeling"
    ],
    "WSI": [
      "whole slide image",
      "word sense induction"
    ],
    "CDA": [
      "concurrent dialogue acts",
      "christen democratisch appel",
      "canonical discriminant analysis",
      "continuous decomposition analysis"
    ],
    "BL": [
      "black level subtraction",
      "bayesian learning"
    ],
    "NSS": [
      "normalized scan - path saliency",
      "non - local self similar"
    ],
    "VSI": [
      "virtual switch instances",
      "variational system identification",
      "voltage source inverter"
    ],
    "RRC": [
      "rank residual constraint",
      "radio resource control"
    ],
    "ASF": [
      "apache software foundation",
      "african swine fever"
    ],
    "AKS": [
      "almost known sets",
      "asimmetric kernel scaling"
    ],
    "ICE": [
      "intrinsic control error",
      "interactive connectivity establishment"
    ],
    "PDP": [
      "partial dependence plots",
      "product display page",
      "policy decision point"
    ],
    "RD": [
      "real data",
      "residual denoiser",
      "research and development",
      "relative difference",
      "reciprocal degree"
    ],
    "IT": [
      "iris thickness",
      "immediate threshold",
      "inferior temporal",
      "image translation"
    ],
    "CBP": [
      "coprime blur pairs",
      "compact bilinear pooling"
    ],
    "RFS": [
      "random finite set",
      "rain fog snow"
    ],
    "IFD": [
      "indian face database",
      "icelandic frequency dictionary"
    ],
    "CDR": [
      "call detail records",
      "critical design review",
      "clock difference relations"
    ],
    "DBP": [
      "discrete base problem",
      "determinisable by pruning",
      "digital back propagation"
    ],
    "BLE": [
      "bluetooth low energy",
      "bilingual lexicon extraction"
    ],
    "RTF": [
      "region templates framework",
      "real time factor"
    ],
    "BSP": [
      "binary space partitioning",
      "bulk synchronous parallel"
    ],
    "RCA": [
      "root certificate authority",
      "ripple carry adder",
      "root cause analysis",
      "reverse classification accuracy"
    ],
    "LBP": [
      "local binary pattern",
      "loopy belief propagation"
    ],
    "LML": [
      "lifelong metric learning",
      "log marginal likelihood",
      "lifelong machine learning"
    ],
    "ADF": [
      "anisotropic diffusion filter",
      "automatically defined function"
    ],
    "DML": [
      "data modification layer",
      "declarative ml language"
    ],
    "BQ": [
      "basic question",
      "bayesian quadrature"
    ],
    "LA": [
      "logical access",
      "layout analysis",
      "left atrium",
      "location area"
    ],
    "NPR": [
      "near perfect reconstruction",
      "normalized probabilistic rand"
    ],
    "PEP": [
      "permission enforcement point",
      "policy enforcement point"
    ],
    "PPT": [
      "pignistic probability transformation",
      "privacy preserving techniques"
    ],
    "DMA": [
      "direct memory access",
      "dynamic mechanical analysis",
      "data market austria"
    ],
    "SDF": [
      "side - stream dark field",
      "signed distance function",
      "signed distance field"
    ],
    "SU": [
      "symmetric uncertainty",
      "secondary user"
    ],
    "RPG": [
      "relevance proximity graph",
      "robust principal graph"
    ],
    "PIT": [
      "permutation invariant training",
      "pending interest table"
    ],
    "CB": [
      "code block",
      "content - based",
      "circular buffered",
      "compression benchmark",
      "causal box"
    ],
    "DMF": [
      "dynamic mode factorization",
      "drone - cell management frame"
    ],
    "DBA": [
      "dtw barycenter averaging",
      "deterministic buchi automaton"
    ],
    "SRL": [
      "semantic role labeling",
      "state representation learning",
      "statistical relational learning"
    ],
    "RQ": [
      "research question",
      "reformulated queries"
    ],
    "SBM": [
      "stochastic block model",
      "sequential monte carlo",
      "standard bit mutations",
      "shape boltzmann machine"
    ],
    "FJ": [
      "friendly jamming",
      "featherweight java"
    ],
    "SPF": [
      "structure propagation fusion",
      "shortest path forest"
    ],
    "HM": [
      "harmonic mean",
      "hybrid model"
    ],
    "LOD": [
      "linked open data",
      "level of detail"
    ],
    "GTD": [
      "grasp type detection",
      "grasp type dataset"
    ],
    "TCR": [
      "trap control register",
      "transductive cascaded regression"
    ],
    "LE": [
      "low energy",
      "label equivalence"
    ],
    "LCS": [
      "longest common subsequence",
      "local causal states"
    ],
    "FAST": [
      "features from accelerated segment test",
      "file and storage technologies"
    ],
    "SSE": [
      "streaming simd extensions",
      "spherical semantic embedding"
    ],
    "DSR": [
      "dynamic sparse reparameterization",
      "dynamic source routing"
    ],
    "GPM": [
      "graph pattern matching",
      "matchinggraph pattern matching"
    ],
    "VR": [
      "virtual reality",
      "visibility region",
      "vigilance reward"
    ],
    "MPA": [
      "music performance analysis",
      "message passing algorithm"
    ],
    "SAN": [
      "semantic alignment network",
      "saturation analysis",
      "subject alternate name",
      "stacked attention network",
      "self attention network"
    ],
    "SSI": [
      "subspace system identification",
      "social system identification",
      "software sustainability institute"
    ],
    "TDM": [
      "technical debt management",
      "temporal difference model",
      "time division multiplexing"
    ],
    "NS": [
      "network science",
      "negative sampling",
      "neutron star"
    ],
    "SUs": [
      "secondary users",
      "spectrum usage"
    ],
    "PBS": [
      "primary base station",
      "public broadcasting service"
    ],
    "PCL": [
      "positive coalgebraic logics",
      "point cloud library",
      "path consistency learning"
    ],
    "DMN": [
      "dynamic memory network",
      "default mode network"
    ],
    "SFM": [
      "social force model",
      "structural factorization machine",
      "structure from motion"
    ],
    "GF": [
      "guided filtering",
      "gabor filter"
    ],
    "CDP": [
      "centralized differential privacy",
      "classical dynamic programming"
    ],
    "SAM": [
      "semi - autonomous machine",
      "speaker - addressee model",
      "search of associative memory",
      "self - assessment manikin"
    ],
    "TM": [
      "tone mapping",
      "teacher mark",
      "turing machine"
    ],
    "DADA": [
      "distributed affinity dual approximation",
      "dual adversarial domain adaptation"
    ],
    "DEC": [
      "deep embedded clustering",
      "dense - captioning event"
    ],
    "CNL": [
      "controlled natural language",
      "certain natural language"
    ],
    "PIN": [
      "proposal indexing network",
      "phrase indexing network"
    ],
    "USD": [
      "unmet system demand",
      "unambiguous state discrimination"
    ],
    "HC": [
      "healthy control",
      "hill - climbing",
      "hierarchical classification"
    ],
    "GSP": [
      "generalized second price",
      "global statistics pooling"
    ],
    "ESS": [
      "effective sample size",
      "evolutionary stable strategies"
    ],
    "LDS": [
      "low density spreading",
      "linear dynamical system"
    ],
    "ARD": [
      "adversarially robust distillation",
      "automatic relevance determination",
      "accelerated robust distillation"
    ],
    "NL": [
      "network lifetime",
      "natural language"
    ],
    "ILS": [
      "incomplete lineage sorting",
      "iterated local search"
    ],
    "AML": [
      "adversarial machine learning",
      "actor modeling language"
    ],
    "MN": [
      "mobile network",
      "master node",
      "memory networks",
      "mobile node"
    ],
    "SED": [
      "soft edit distance",
      "sound event detection",
      "standard edit distance"
    ],
    "UDP": [
      "user datagram protocol",
      "universal dependency parse"
    ],
    "SSL": [
      "structural sparsity learning",
      "scleral spur location",
      "semi supervised learning"
    ],
    "SCR": [
      "scratch",
      "sparse compositional regression",
      "skin conductance response"
    ],
    "CKA": [
      "concurrent kleene algebra",
      "centered kernel alignment"
    ],
    "RDS": [
      "relational database service",
      "running digital sum"
    ],
    "WF": [
      "white females",
      "weighted fusion"
    ],
    "TBB": [
      "tor browser bundle",
      "threading building blocks"
    ],
    "DI": [
      "document index",
      "dyadic indicator",
      "direct inspection",
      "dependency injection"
    ],
    "TPD": [
      "turbo product decoder",
      "total project delay"
    ],
    "NIC": [
      "neural image caption",
      "network interface card"
    ],
    "DSA": [
      "data science and analytics",
      "digital signature algorithm"
    ],
    "MRS": [
      "magnetic resonance spectroscopy",
      "multiset rewriting systems"
    ],
    "CO": [
      "context - only attention",
      "carbon - oxygen"
    ],
    "NSP": [
      "neural sequence prediction",
      "next sentence prediction"
    ],
    "FG": [
      "favoured granted",
      "filter gate"
    ],
    "BSC": [
      "binary symmetric channel",
      "base station controller"
    ],
    "BSD": [
      "blind spot detection",
      "berkeley segmentation dataset"
    ],
    "FPS": [
      "frame per second",
      "false projection selection"
    ],
    "SPS": [
      "signal processing systems",
      "surcharge pricing scheme",
      "signal probability skey"
    ],
    "PPE": [
      "per - pixel - error",
      "predictive performance equation"
    ],
    "EMS": [
      "elevated mean scan statistic",
      "event management system",
      "elevated mean scan"
    ],
    "FAR": [
      "false acceptance rate",
      "flow annotation replanning"
    ],
    "CFD": [
      "computational fluid dynamics",
      "carrier frequency difference"
    ],
    "DSO": [
      "direct sparse odometry",
      "distribution system operator"
    ],
    "DTP": [
      "difference target propagation",
      "dynamic trajectory predictor"
    ],
    "GI": [
      "gradient initialization",
      "graph isomorphism"
    ],
    "SSS": [
      "staggered sample selection",
      "stochastically stable states"
    ],
    "DST": [
      "dialogue state tracker",
      "discrete sine transform"
    ],
    "ID": [
      "item description",
      "information decoding",
      "input data",
      "interleaved declustering"
    ],
    "FEA": [
      "factored evolutionary algorithms",
      "finite element analysis"
    ],
    "SB": [
      "systems biology",
      "symmetry breaking"
    ],
    "SG": [
      "skip gram",
      "stochastic gradient"
    ],
    "CLT": [
      "central limit theorem",
      "cognitive load theory"
    ],
    "MET": [
      "michigan english test",
      "multi - edge type"
    ],
    "GSR": [
      "geographic source routing",
      "group sparsity residual",
      "group sparse representation"
    ],
    "GPR": [
      "gaussian process regression",
      "gamma passing rate"
    ],
    "STA": [
      "static timing analysis",
      "super - twisting algorithms"
    ],
    "HMC": [
      "hybrid monte carlo",
      "hamiltonian monte carlo"
    ],
    "LSM": [
      "laplacian - based shape matching",
      "lock sweeping method"
    ],
    "IO": [
      "inverse optimization",
      "iterative optimization",
      "interacting object"
    ],
    "LAP": [
      "low altitude platform",
      "linear assignment problem"
    ],
    "LTP": [
      "licklider transmission protocol",
      "long term potentiation"
    ],
    "GMS": [
      "grid - based motion statistics",
      "gaussian material synthesis"
    ],
    "DCM": [
      "dynamics canalization map",
      "discontinuous conduction mode",
      "deep choice model",
      "discrete choice models",
      "device configuration manager"
    ],
    "MGE": [
      "minimum generation error",
      "multi - granularity embedding"
    ],
    "MCS": [
      "maximal consistent set",
      "modulation and coding scheme",
      "maximum cardinality search"
    ],
    "OP": [
      "orthogonal procrustes",
      "old persian",
      "outage probability",
      "original precision",
      "orienteering problem"
    ],
    "CWE": [
      "common weakness enumeration",
      "character - enhanced word embedding",
      "chinese word embeddings"
    ],
    "MSR": [
      "minimum storage regenerating",
      "mining software repositories"
    ],
    "PT": [
      "piecewise -testable",
      "physical therapy",
      "productive time",
      "proof time"
    ],
    "PBRT": [
      "physically based renderer",
      "physically based ray tracing"
    ],
    "NHS": [
      "national health service",
      "nurses ' health study"
    ],
    "LSC": [
      "leicester scientific corpus",
      "long skip connections"
    ],
    "STL": [
      "single task learning",
      "signal temporal logic",
      "standard template library"
    ],
    "SBS": [
      "swedish blog sentences",
      "small - cell base stations"
    ],
    "PAA": [
      "piecewise aggregation approximation",
      "principal axis analysis"
    ],
    "CPS": [
      "common phone set",
      "current population survey"
    ],
    "MVP": [
      "mitral valve prolapse",
      "million veterans program"
    ],
    "MPB": [
      "matrix pair beamformer",
      "modified poisson blending"
    ],
    "MIS": [
      "multiple importance sampling",
      "maximal independent set"
    ],
    "LF": [
      "large faces",
      "late fusion",
      "line feeds"
    ],
    "SOC": [
      "security operations center",
      "standard occupation classification",
      "state of charge"
    ],
    "IVR": [
      "interactive voice response",
      "immersive virtual reality"
    ],
    "IA": [
      "intent analyst",
      "interval analysis",
      "incremental approximation",
      "interference alignment"
    ],
    "IFT": [
      "information foraging theory",
      "information flow tracking"
    ],
    "ARS": [
      "augmented random search",
      "addressee and response selection"
    ],
    "SCS": [
      "statistical compressed sensing",
      "shortest common superstring",
      "spoken conversational search",
      "sub - carrier spacing"
    ],
    "SQA": [
      "semantic question answering",
      "spoken question answering"
    ],
    "AWE": [
      "averaged word embeddings",
      "address windowing extensions"
    ],
    "TAS": [
      "transverse abdominal section",
      "transmit antenna selection"
    ],
    "IE": [
      "information extraction",
      "intelligent element",
      "integral equation"
    ],
    "CEM": [
      "causal effect map",
      "circled entropy measurement",
      "cross entropy methods"
    ],
    "UM": [
      "user model",
      "upsampling module"
    ],
    "ILM": [
      "internal limiting membrane",
      "information lifecycle management"
    ],
    "RGB": [
      "red , green , blue",
      "red giant branch"
    ],
    "CSG": [
      "cumulative spectral gradient",
      "cost sharing game"
    ],
    "PPC": [
      "peak power contract",
      "pay per click"
    ],
    "EMG": [
      "eight medical grade",
      "electromyograph"
    ],
    "DSP": [
      "digital signal processing",
      "discrete sequence production"
    ],
    "MVF": [
      "maximum voice frequency",
      "matching vector families"
    ],
    "FDA": [
      "fisher 's discriminant analysis",
      "functional data analysis"
    ],
    "TDA": [
      "topological data analysis",
      "targeted degree - based attack"
    ],
    "ERB": [
      "equivalent rectangular bandwidth",
      "enhanced residual block"
    ],
    "EHS": [
      "enhanced hybrid simultaneous",
      "enhanced hybrid swipt protocol"
    ],
    "SIR": [
      "sequential importance resampling",
      "source to interferences ratio"
    ],
    "EMF": [
      "explicit matrix factorization",
      "eclipse modeling framework",
      "electromagnetic fields"
    ],
    "DLS": [
      "derandomized local search",
      "depth - limited search"
    ],
    "AIDA": [
      "analytic imaging diagnostics arena",
      "atomic , independent , declarative , and absolute"
    ],
    "NTM": [
      "neural turing machine",
      "neural topic model"
    ],
    "DNS": [
      "domain name system",
      "domain name service"
    ],
    "EF": [
      "expedited forwarding",
      "ejection fraction",
      "error feedback"
    ],
    "MTC": [
      "movie triplets corpus",
      "machine type communications"
    ],
    "ISM": [
      "interactive skill modules",
      "industrial , scientific and medical"
    ],
    "PTS": [
      "partial transmit sequences",
      "public transportation system"
    ],
    "PDT": [
      "pulse discrete time",
      "poisson delaunay tessellations"
    ],
    "PWM": [
      "pulse width modulation",
      "partial weighted matching"
    ],
    "GCD": [
      "graphlet correlation distance",
      "greatest common divisor"
    ],
    "CCG": [
      "calling contexts graphs",
      "combinatory categorial grammar",
      "chromatic correction gratings"
    ],
    "MCP": [
      "mean closest points",
      "matern cluster process"
    ],
    "OR": [
      "optic radiation",
      "operations research",
      "opportunistic relaying"
    ],
    "DPN": [
      "dual path network",
      "deep pyramid network"
    ],
    "LTT": [
      "lunar transfer trajectory",
      "locally threshold testable"
    ],
    "MED": [
      "minimal edit distance",
      "multimedia event detection"
    ],
    "FER": [
      "frame error rate",
      "facial expression recognition"
    ],
    "AE": [
      "autoencoder",
      "associative experiment",
      "absolute error",
      "answer extraction"
    ],
    "BPP": [
      "bits per pixel",
      "binomial point process"
    ],
    "APD": [
      "average perpendicular distance",
      "artifact pyramid decoding"
    ],
    "SEM": [
      "scanning electron microscopy",
      "squared entropy measurement",
      "simple event model"
    ],
    "PTM": [
      "point - to - multipoint",
      "persistent turing machine"
    ],
    "CWT": [
      "continuous wavelet transform",
      "complex wavelet transform"
    ],
    "TA": [
      "transmission antennas",
      "threshold algorithm"
    ],
    "HOG": [
      "histogram of gradients",
      "histogram of oriented gradient"
    ],
    "NCE": [
      "normalized cumulative entropy",
      "noise contrastive estimation"
    ],
    "EP": [
      "entrance pupil",
      "exponent parikh",
      "efficient path",
      "evolutionary programming",
      "europarl"
    ],
    "COP": [
      "correlated orienteering problem",
      "centralized optimization problem"
    ],
    "QMA": [
      "quantitative myotonia assessment",
      "quantum merlin arthur"
    ],
    "MRT": [
      "minimum risk training",
      "maximum ratio transmission"
    ],
    "VCC": [
      "vibrational coupled cluster",
      "vehicular cloud computing"
    ],
    "RIC": [
      "restricted isometry constant",
      "risk inflation criterion"
    ],
    "MV": [
      "mitral valve",
      "memory vector"
    ],
    "OCT": [
      "optical coherence tomography",
      "odd cycle transversal"
    ],
    "OA": [
      "open access",
      "ocular artifacts",
      "orthogonal array"
    ],
    "TBA": [
      "targeted betweenness - based attack",
      "tailor based allocation"
    ],
    "IDE": [
      "integrated development environment",
      "interprocedural distributive environment"
    ],
    "DCH": [
      "dynamic competition hypothesis",
      "discriminant cross - modal hashing"
    ],
    "GAM": [
      "generalized additive models",
      "generative adversarial metric"
    ],
    "TVD": [
      "total variation diminishing",
      "threshold voltage defined"
    ],
    "RUM": [
      "random utility modelwe",
      "random utility maximization"
    ],
    "TRI": [
      "temporal random indexing",
      "toyota research institute"
    ],
    "QR": [
      "quantile regression",
      "quadruple range"
    ],
    "MB": [
      "motion blurring",
      "model - based",
      "maximal biclique"
    ],
    "AFC": [
      "atomic function computation",
      "automated fare collection(afc",
      "automatic fact checking"
    ],
    "PSL": [
      "power service layer",
      "probabilistic soft logic"
    ],
    "RPL": [
      "recurrent power law",
      "routing protocol for low - power and lossy networks"
    ],
    "SPAM": [
      "subtractive pixel adjacency matrix",
      "state preparation and measurement errors"
    ],
    "PSM": [
      "patient side manipulator",
      "precoding - aided spatial modulation"
    ],
    "NI": [
      "new instances",
      "neat image",
      "national instruments",
      "noun incorporation",
      "network interface"
    ],
    "OPF": [
      "optimal power flow",
      "optimal pareto front"
    ],
    "DTN": [
      "delay tolerant networks",
      "domain transfer network",
      "disruption tolerant networking"
    ],
    "PVI": [
      "parabolic variational inequality",
      "perpendicular vegetation index"
    ],
    "ERR": [
      "expected reciprocal rank",
      "exact recovery ratio"
    ],
    "HI": [
      "hubert 's index",
      "histogram intersection"
    ],
    "TCA": [
      "temporal concept analysis",
      "task component architecture"
    ],
    "NUC": [
      "normalized uniformity coefficient",
      "next utterance classification"
    ],
    "OCM": [
      "oz computation model",
      "original component manufacturers"
    ],
    "CCP": [
      "cross conformal prediction",
      "convex - concave procedure"
    ],
    "JD": [
      "joint decoding",
      "joint diagonalization"
    ],
    "LDE": [
      "local discriminant embedding",
      "learnable dictionary encoding"
    ],
    "UC": [
      "universal composability",
      "unit commitment"
    ],
    "CPD": [
      "concave points detection",
      "coherent point drift",
      "coal mine disaster"
    ],
    "HDT": [
      "header dictionary triple",
      "header , dictionary , triples"
    ],
    "SSC": [
      "shapley share coefficient",
      "sparse subspace clustering",
      "similarity sensitive coding"
    ],
    "PDM": [
      "pulse density modulated",
      "probability distribution matrix"
    ],
    "UCM": [
      "use case map",
      "ultrametric contour map"
    ],
    "ZTD": [
      "zenith total delay",
      "zenithal tropospheric delays"
    ],
    "FCA": [
      "formal concept analysis",
      "forward capacity auctions"
    ],
    "BU": [
      "bottom - up",
      "bandwidth units"
    ],
    "BCL": [
      "boolean coalgebraic logics",
      "bilateral convolutional layers"
    ],
    "AQG": [
      "analyze questions generated",
      "automatic question generation"
    ],
    "CSE": [
      "cumulative spectrum energy",
      "common subexpression elimination"
    ],
    "MRD": [
      "mean rank difference",
      "maximal ratio diversity"
    ],
    "NEM": [
      "net energy metering",
      "new economy movement"
    ],
    "CLI": [
      "command line interface",
      "cuneiform language identification"
    ],
    "MPCA": [
      "mobility prediction clustering algorithm",
      "multi - linear principal components analysis"
    ],
    "QF": [
      "query fusion",
      "quality factor",
      "quadratic form"
    ],
    "BOA": [
      "butterfly optimization algorithm",
      "bilevel optimization algorithm"
    ],
    "HP": [
      "high prr",
      "hawkes processes"
    ],
    "CAA": [
      "civil aviation authority",
      "clump assignment array"
    ],
    "ACI": [
      "adjacent channel interference",
      "artificial collective intelligence"
    ],
    "OBS": [
      "optical burst - switched",
      "optimal brain surgeon"
    ]
  }