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| A* | A* Search Algorithm | |
|---|---|---|
| A/B Testing | A statistical method for comparing two or more treatments or algorithms | |
| A3C | Asynchronous Advantage Actor-Critic | |
| ABAC | Attribute-Based Access Control | |
| ACE | Alternating conditional expectation algorithm | |
| ACO | Ant Colony Optimization | |
| AdA | Adaptive Agent | |
| Adam | Adaptive Moment Estimation | |
| ADASYN | Adaptive Synthetic Sampling | |
| ADT | Automatic Drum Transcription | |
| AE | Autoencoder | |
| AGC | Adaptive Gradient Clipping | |
| AGI | Artificial general intelligence | |
| AI | Artificial intelligence | |
| AIaaS | Artificial Intelligence as a Service | |
| AIWPSO | Adaptive Inertia Weight Particle Swarm Optimization | |
| AL | Active Learning | |
| AM | Activation maximization | |
| AMR | Abstract Meaning Representation | |
| AMT | Automatic Music Transcription | |
| ANI | Artificial Narrow Intelligence | |
| ANN | Artificial neural network | |
| ANOVA | Analysis of variance | |
| API | Application Programming Interface | |
| AR | Augmented reality | |
| ARNN | Anticipation Recurrent Neural Network | |
| ASI | Artificial superintelligence | |
| ASIC | Application-Specific Integrated Circuit | |
| ASR | Automatic speech recognition | |
| AST | Automated speech translation | |
| AUC | Area Under the Curve | |
| AutoML | Automated Machine Learning | |
| BB84 | A quantum key distribution protocol (named after its inventors, Bennett and Brassard, and the year 1984) | |
| BBO | Biogeography-Based Optimization | |
| BCE | Binary cross-entropy | |
| BDT | Boosted Decision Tree | |
| BERT | Bidirectional Encoder Representations from Transformers | |
| BFS | Breadth-First Search | |
| BI | Business Intelligence | |
| BiFPN | Bidirectional Feature Pyramid Network | |
| BILSTM | Bidirectional Long Short-Term Memory | |
| BLEU | Bilingual evaluation understudy | |
| BN | Bayesian Network | |
| BNN | Bayesian Neural Network | |
| BO | Bayesian Optimization | |
| BP | Backpropagation | |
| BPE | Byte Pair Encoding | |
| BPMF | Bayesian Probabilistic Matrix Factorization | |
| BPN | Backpropagation Neural Network | |
| BPTT | Backpropagation through time | |
| BQML | Big Query Machine Learning | |
| BR | Best-Response (in game theory) | |
| BRDF | Bidirectional reflectance distribution function | |
| BRNN | Bidirectional Recurrent Neural Network | |
| BRR | Bayesian ridge regression | |
| CAD | Computer-Aided Design | |
| CAE | Contractive Autoencoder | |
| CALA | Continuous Action-set Learning Automata | |
| CAM | Computer-Aided Manufacturing | |
| CAPTCHA | Completely Automated Public Turing test to tell Computers and Humans Apart | |
| CART | Classification And Regression Tree | |
| CASE | Computer-Aided Software Engineering | |
| CatBoost | Categorical Boosting | |
| CAV | Concept Activation Vectors | |
| CBAC | Content-Based Access Control | |
| CBI | Counterfactual Bias Insertion | |
| CBOW | Continuous Bag of Words | |
| CBR | Case-Based Reasoning | |
| CCA | Canonical Correlation Analysis | |
| CCC | Canonical Correlation Coefficients | |
| CCE | Categorical cross-entropy | |
| CDBN | Convolutional Deep Belief Networks | |
| CE | Cross-Entropy | |
| CEC | Constant Error Carousel | |
| CEGAR | Counterexample-Guided Abstraction Refinement | |
| CEGIS | Counterexample-Guided Inductive Synthesis | |
| CF | Common Features | |
| cGAN | Conditional Generative Adversarial Network | |
| CL | Confident learning | |
| CLIP | Contrastive Language-Image Pre-Training | |
| CLNN | ConditionaL Neural Networks | |
| CMA | Covariance Matrix Adaptation | |
| CMA-ES | Covariance Matrix Adaptation Evolution Strategy | |
| CMAC | Cerebellar Model Articulation Controller | |
| CMMs | Conditional Markov Model | |
| CNN | Convolutional neural network | |
| COIN-OR | Computational Infrastructure for Operations Research | |
| ConvNet | Convolutional Neural Network | |
| COT | Chain of Thought | |
| COTE | Collective of Transformation-Based Ensembles | |
| COTP | Chain of Thought Prompting | |
| CP | Constraint Programming | |
| CPLEX | An optimization solver (from "C" programming language and "simplex") | |
| CPN | Colored Petri Nets | |
| CRBM | Conditional Restricted Boltzmann Machine | |
| CRF | Conditional Random Field | |
| CRFs | Conditional Random Fields | |
| CRNN | Convolutional Recurrent Neural Network | |
| CSLR | Continuous Sign Language Recognition | |
| CSP | Constraint Satisfaction Problem | |
| CSV | Comma-separated values | |
| CT-LSTM | Convolutional Transformer Long Short-Term Memory | |
| CTC | Connectionist Temporal Classification | |
| CTR | Collaborative Topic Regression | |
| CUDA | Compute Unified Device Architecture | |
| CV | Computer Vision, Cross validation, Coefficient of variation | |
| Cyc | CycL and OpenCyc, a knowledge representation and reasoning system | |
| D* | Dynamic A* Search Algorithm | |
| DAAF | Data Augmentation and Auxiliary Feature | |
| DaaS | Data as a Service | |
| DAE | Denoising AutoEncoder or Deep AutoEncoder | |
| DAML | DARPA Agent Markup Language | |
| DART | Disturbance Aware Regression Tree | |
| DBM | Deep Boltzmann Machine | |
| DBN | Deep belief network | |
| DBSCAN | Density-Based Spatial Clustering of Applications with Noise | |
| DCAI | Data-centric AI | |
| DCGAN | Deep Convolutional Generative Adversarial Network | |
| DCMDN | Deep Convolutional Mixture Density Network | |
| DDPG | Deep Deterministic Policy Gradient | |
| DE | Differential evolution | |
| DeconvNet | DeConvolutional Neural Network | |
| DeepLIFT | Deep Learning Important FeaTures | |
| DFS | Depth-First Search | |
| DL | Deep learning | |
| DM | Diffusion model | |
| DNN | Deep neural network | |
| DP | Dynamic Programming | |
| DQN | Deep Q-Learning | |
| DR | Detection Rate | |
| DRL | Deep Reinforcement Learning | |
| DS | Data Science | |
| DSN | Deep Stacking Network | |
| DSR | Deep Symbolic Reinforcement Learning | |
| DSS | Decision Support System | |
| DSW | Data Stream Warehousing | |
| DT | Decision Tree | |
| DTD | Deep Taylor Decomposition | |
| DWT | Discrete Wavelet Transform | |
| EDA | Exploratory data analysis | |
| EKF | Extended Kalman Filter | |
| ELECTRA | Efficiently Learning an Encoder that Classifies Token Replacements Accurately | |
| ELM | Extreme Learning Machine | |
| ELMo | Embeddings from Language Models | |
| ELU | Exponential Linear Unit | |
| EM | Expectation maximization | |
| EMD | Entropy Minimization Discretization | |
| ERNIE | Enhanced Representation through kNowledge IntEgration | |
| ES | Evolution Strategies | |
| ESN | Echo State Network | |
| ETL | Extract, Transform, Load | |
| ETL Pipeline | Extract Transform Load Pipeline | |
| EXT | Extremely Randomized Trees | |
| F1 | F1 Score (harmonic mean of precision and recall) | |
| F1 Score | Harmonic Precision-Recall Mean | |
| FALA | Finite Action-set Learning Automata | |
| Fast R-CNN | Faster Region-based Convolutional Neural Network | |
| FC | Fully-Connected | |
| FC-CNN | Fully Convolutional Convolutional Neural Network | |
| FC-LSTM | Fully Connected Long Short-Term Memory | |
| FCM | Fuzzy C-Means | |
| FCN | Fully Convolutional Network | |
| FER | Facial Expression Recognition | |
| FFT | Fast Fourier transform | |
| FL | Federated Learning | |
| FLOP | Floating Point Operations | |
| FLOPS | Floating Point Operations Per Second | |
| FM | Foundation model | |
| FN | False negative | |
| FNN | Feedforward Neural Network | |
| FNR | False negative rate | |
| FOAF | Friend of a Friend (ontology) | |
| FP | False positive | |
| FPGA | Field-Programmable Gate Array | |
| FPN | Feature Pyramid Network | |
| FPR | False positive rate | |
| FST | Finite state transducer | |
| FTL | Few-Shot Learning | |
| FWA | Fireworks Algorithm | |
| FWIoU | Frequency Weighted Intersection over Union | |
| GA | Genetic Algorithm | |
| GALE | Global Aggregations of Local Explanations | |
| GAM | Generalized Additive Model | |
| GAN | Generative Adversarial Network | |
| GAP | Global Average Pooling | |
| GQA | Grouped-Query Attention | |
| GBDT | Gradient Boosted Decision Tree | |
| GBM | Gradient Boosting Machine | |
| GBRCN | Gradient-Boosting Random Convolutional Network | |
| GD | Gradient descent | |
| GEBI | Global Explanation for Bias Identification | |
| GFNN | Gradient frequency neural network | |
| GLCM | Gray Level Co-occurrence Matrix | |
| GLM | Generalized Linear Model | |
| GLOM | A neural network architecture by Geoffrey Hinton | |
| Gloss2Text | A task of transforming raw glosses into meaningful sentences. | |
| GloVE | Global Vectors | |
| GLPK | GNU Linear Programming Kit | |
| GLUE | General Language Understanding Evaluation | |
| GMM | Gaussian mixture model | |
| GP | Genetic Programming | |
| GPR | Gaussian process regression | |
| GPT | Generative Pre-Training | |
| GPU | Graphics processing unit | |
| GradCAM | GRADient-weighted Class Activation Mapping | |
| GRU | Gated recurrent unit | |
| Gurobi | An optimization solver (named after its founders, Zonghao Gu, Edward Rothberg, and Robert Bixby) | |
| HamNoSys | Hamburg Sign Language Notation System | |
| HAN | Hierarchical Attention Networks | |
| HC | Hierarchical Clustering | |
| HCA | Hierarchical Clustering Analysis | |
| HDP | Hierarchical Dirichlet process | |
| HF | Hugging Face | |
| HHDS | HipHop Dataset | |
| hLDA | Hierarchical Latent Dirichlet allocation | |
| HMM | Hidden Markov Model | |
| HNN | Hopfield Neural Network | |
| HOG | Histogram of Oriented Gradients (feature descriptor) | |
| Hopfield | Hopfield Network | |
| HPC | High Performance Computing | |
| HRED | Hierarchical Recurrent Encoder-Decoder | |
| HRI | Human-Robot Interaction | |
| HSMM | Hidden Semi-Markov Model | |
| HTM | Hierarchical Temporal Memory | |
| i.i.d | Independent and Identically Distributed | |
| i.i.d. | Independently and identically distributed | |
| IaaS | Infrastructure as a Service | |
| ICA | Independent component analysis | |
| ICP | Iterative Closest Point (point cloud registration) | |
| ID3 | Iterative Dichotomiser 3 | |
| IDA* | Iterative Deepening A* Search Algorithm | |
| IDR | Input dependence rate | |
| IG | Invariant Generation | |
| IID | Independently and identically distributed | |
| IIR | Input independence rate | |
| ILASP | Inductive Learning of Answer Set Programs | |
| ILP | Integer Linear Programming | |
| INFD | Explanation Infidelity | |
| IoA | Internet of Agents | |
| IoE | Internet of Everything | |
| IoT | Internet of Things | |
| IoU | Jaccard index (intersection over union) | |
| IR | Information Retrieval | |
| IRCoT | Interleaving Retrieval CoT | |
| ISIC | International Skin Imaging Collaboration | |
| IVR | Interactive Voice Response | |
| K-Means | K-Means Clustering | |
| KB | Knowledge Base | |
| KDE | Kernel Density Estimation | |
| KF | Kalman Filter | |
| kFCV | K-fold cross validation | |
| KL | Kullback Leibler (KL) divergence | |
| KNN | K-nearest neighbors | |
| KR | Knowledge Representation | |
| KRR | Kernel Ridge Regression | |
| LAION | Large-scale Artificial Intelligence Open Network | |
| LAMA | LAnguage Model Analysis | |
| LaMDA | Language Models for Dialog Applications | |
| LBP | Local Binary Pattern (texture descriptor) | |
| LDA | Latent Dirichlet Allocation | |
| LDADE | Latent Dirichlet Allocation Differential Evolution | |
| LEPOR | Language Evaluation Portal | |
| LightGBM | Light Gradient Boosting Machine | |
| LIME | Local Interpretable Model-agnostic Explanations | |
| LINGO | A software for linear, nonlinear, and integer optimization | |
| LL | Lifelong learning | |
| LLM | Large language model | |
| LLS | Linear least squares | |
| LMNN | Large Margin Nearest Neighbor | |
| LoLM | Lots of Little Models | |
| LP | Linear Programming | |
| LPAQA | Language model Prompt And Query Archive | |
| LRP | Layer-wise Relevance Propagation | |
| LSA | Latent semantic analysis | |
| LSI | Latent Semantic Indexing | |
| LSTM | Long short-term memory | |
| LSTM-CRF | Long Short-Term Memory with Conditional Random Field | |
| LTR | Learning To Rank | |
| LVQ | Learning Vector Quantization | |
| M2M | Machine to Machine | |
| MADE | Masked Autoencoder for Distribution Estimation | |
| MAE | Mean absolute error | |
| MAF | Masked Autoregressive Flows | |
| MAIRL | Multi-Agent Inverse Reinforcement Learning | |
| MAP | Maximum A Posteriori (MAP) Estimation | |
| MAPE | Mean absolute percentage error | |
| MARL | Multi-Agent Reinforcement Learning | |
| MART | Multiple Additive Regression Tree | |
| MaxEnt | Maximum Entropy | |
| MAXSAT | Maximum Satisfiability Problem | |
| MCLNN | Masked ConditionaL Neural Networks | |
| MCMC | Markov Chain Monte Carlo | |
| MCS | Model contrast score | |
| MCTS | Monte Carlo Tree Search | |
| MDL | Minimum description length (MDL) principle | |
| MDN | Mixture Density Network | |
| MDP | Markov Decision Process | |
| MDRNN | Multidimensional recurrent neural network | |
| MER | Music Emotion Recognition | |
| METEOR | Metric for Evaluation of Translation with Explicit ORdering | |
| MIL | Multiple Instance Learning | |
| MILP | Mixed-Integer Linear Programming | |
| MINT | Mutual Information based Transductive Feature Selection | |
| MIoU | Mean Intersection over Union | |
| MIP | Mixed-Integer Programming | |
| ML | Machine learning | |
| MLaaS | Machine Learning as a Service | |
| MLE | Maximum Likelihood Estimation | |
| MLLM | Multimodal large language model | |
| MLM | Music Language Models | |
| MLP | Multi-Layer Perceptron | |
| MoA | Mixture of Agents | |
| MoE | Mixture of Experts | |
| MMI | Maximum Mutual Information | |
| MNIST | Modified National Institute of Standards and Technology | |
| MOEA | Multi-Objective Evolutionary Algorithm | |
| MQA | Multi-Query Attention | |
| MPA | Mean Pixel Accuracy | |
| MR | Mixed Reality | |
| MRF | Markov Random Field | |
| MRR | Mean Reciprocal Rank | |
| MRS | Music Recommender System | |
| MSDAE | Modified Sparse Denoising Autoencoder | |
| MSE | Mean squared error | |
| MSR | Music Style Recognition | |
| MTL | Multi-Task Learning | |
| NARX | Nonlinear AutoRegressive with eXogenous input (neural network model) | |
| NAS | Neural Architecture Search | |
| NB | Na ̈ıve Bayes | |
| NBKE | Na ̈ıve Bayes with Kernel Estimation | |
| NDCG | Normalized Discounted Cumulative Gain | |
| NE | Nash Equilibrium (in game theory) | |
| NEAT | NeuroEvolution of Augmenting Topologies | |
| NER | Named entity recognition | |
| NERQ | Named Entity Recognition in Query | |
| NEST | Neural Simulation Tool | |
| NF | Normalizing Flow | |
| NFL | No Free Lunch (NFL) theorem | |
| NISQ | Noisy Intermediate-Scale Quantum (quantum computing) | |
| NLG | Natural Language Generation | |
| NLP | Natural Language Processing | |
| NLT | Neural Machine Translation | |
| NLU | Natural Language Understanding | |
| NMF | Non-negative matrix factorization | |
| NMS | Non Maximum Suppression | |
| NMT | Neural Machine Translation | |
| NN | Neural network | |
| NNMODFF | Neural Network based Multi-Onset Detection Function Fusion | |
| NPE | Neural Physical Engine | |
| NRMSE | Normalized RMSE | |
| NSGA-II | Non-dominated Sorting Genetic Algorithm II | |
| NST | Neural style transfer | |
| NTM | Neural Turing Machine | |
| NuSVC | Nu-Support Vector Classification | |
| NuSVR | Nu-Support Vector Regression | |
| OBM | One Big Model | |
| OCR | Optical character recognition | |
| OD | Object Detection | |
| ODF | Onset Detection Function | |
| OIL | Ontology Inference Layer | |
| OLR | Ordinary Linear Regression | |
| OLS | Ordinary Least Squares | |
| OMNeT++ | Objective Modular Network Testbed in C++ | |
| OMR | Optical Mark Recognition | |
| OOF | Out-of-fold | |
| ORB | Oriented FAST and Rotated BRIEF (feature descriptor) | |
| OWL | Web Ontology Language | |
| PA | Pixel Accuracy | |
| PaaS | Platform as a Service | |
| PACO | Poisson Additive Co-Clustering | |
| PaLM | Pathways Language Model | |
| PBAC | Policy-Based Access Control | |
| PCA | Principal component analysis | |
| PCL | Point Cloud Library (3D perception) | |
| PECS | Physics Engine for Collaborative Simulation | |
| PEGASUS | Pre-training with Extracted Gap-Sentences for Abstractive Summarization | |
| PF | Particle Filter | |
| PFE | Probabilistic facial embedding | |
| PLSI | Probabilistic Latent Semantic Indexing | |
| PM | Project Manager | |
| PMF | Probabilistic Matrix Factorization | |
| PMI | Pointwise Mutual Information | |
| PNN | Probabilistic Neural Network | |
| POC | Proof of Concept | |
| POMDP | Partially Observable Markov Decision Process | |
| POS | Part of Speech (POS) Tagging | |
| POT | Partially Observable Tree (decision-making under uncertainty) | |
| PPL | Perplexity (a measure of language model performance) | |
| PPMI | Positive Pointwise Mutual Information | |
| PPO | Proximal Policy Optimization | |
| PReLU | Parametric Rectified Linear Unit-Yor Topic Modeling | |
| PRM | Probabilistic Roadmap (motion planning algorithm) | |
| PSO | Particle Swarm Optimization | |
| PU | Positive Unlabaled | |
| PYTM | Pitman | |
| QA | Question Answering | |
| QAOA | Quantum Approximate Optimization Algorithm | |
| QAP | Quadratic Assignment Problem | |
| QEC | Quantum Error Correction | |
| QFT | Quantum Fourier Transform | |
| QIP | Quantum Information Processing | |
| QKD | Quantum Key Distribution | |
| QML | Quantum Machine Learning | |
| QNN | Quantum Neural Network | |
| QP | Quadratic Programming | |
| QPE | Quantum Phase Estimation | |
| R-CNN | Region-based Convolutional Neural Network | |
| R2 | R-squared | |
| RAG | Retrieval-Augmented Generation | |
| RandNN | Random Neural Network | |
| RANSAC | RANdom SAmple Consensus | |
| RBAC | Rule-Based Access Control | |
| RBF | Radial Basis Function | |
| RBFNN | Radial Basis Function Neural Network | |
| RBM | Restricted Boltzmann Machine | |
| RDF | Resource Description Framework | |
| ReAct | Reason + Act | |
| REALM | Retrieval-Augmented Language Model Pre-Training | |
| ReCAPTCHA | Reverse CAPTCHA | |
| ReLU | Rectified Linear Unit | |
| REPTree | Reduced Error Pruning Tree | |
| RETRO | Retrieval Enhanced Transformer | |
| RF | Random forest | |
| RFE | Recursive Feature Elimination | |
| RGB | Red Green Blue color model | |
| RICNN | Rotation Invariant Convolutional Neural Network | |
| RIM | Recurrent Interence Machines | |
| RIPPER | Repeated Incremental Pruning to Produce Error Reduction | |
| RISE | Random Interval Spectral Ensemble | |
| RL | Reinforcement learning | |
| RLFM | Regression based latent factors | |
| RLHF | Reinforcement Learning from Human Feedback | |
| RMSE | Root mean squared error | |
| RMSLE | Root mean squared logarithmic error | |
| RMSprop | Root Mean Square Propagation | |
| RNN | Recurrent neural network | |
| RNNLM | Recurrent Neural Network Language Model (RNNLM) | |
| RoBERTa | Robustly Optimized BERT Pretraining Approach | |
| ROC | Receiver operating characteristic | |
| ROI | Region Of Interest | |
| ROS | Robot Operating System | |
| ROUGE | Recall-Oriented Understudy for Gisting Evaluation (NLP metric) | |
| RPA | Robotic Process Automation | |
| RR | Ridge Regression | |
| RRT | Rapidly-exploring Random Tree (motion planning algorithm) | |
| RSI | Recursive self-improvement | |
| RTRL | Real-Time Recurrent Learning | |
| SA | Simulated Annealing, Segment Anything | |
| SAM | Segment Anything Model | |
| SaaS | Software as a Service | |
| SAC | Soft Actor-Critic | |
| SAE | Stacked AE | |
| SARSA | State-Action-Reward-State-Action | |
| SAT | Satisfiability Problem | |
| SBAC | Situation-Based Access Control | |
| SBM | Stochastic block model | |
| SBO | Structured Bayesian optimization | |
| SBSE | Search-based software engineering | |
| SCH | Stochastic convex hull | |
| SCIP | Solving Constraint Integer Programs | |
| SDAE | Stacked DAE | |
| seq2seq | Sequence to Sequence Learning | |
| SER | Sentence Error Rate | |
| SGBoost | Stochastic Gradient Boosting | |
| SGD | Stochastic gradient descent | |
| SGVB | Stochastic Gradient Variational Bayes | |
| SHAP | SHapley Additive exPlanation | |
| SHLLE | Supervised Hessian Locally Linear Embedding | |
| SIFT | Scale-Invariant Feature Transform (feature detection) | |
| Sign2(Gloss+Text) | Sign to Gloss and Text | |
| Sign2Gloss | A one to one translation from the single sign to the single gloss. | |
| Sign2Text | A task of full translation from the sign language into the spoken one | |
| SL | Supervised learning | |
| SLAM | Simultaneous Localization and Mapping | |
| SLM | Small Language Model | |
| SLDS | Switching Linear Dynamical System | |
| SLP | Single-Layer Perceptron | |
| SLRT | Sign Language Recognition Transformer | |
| SLT | Sign Language Translation | |
| SLTT | Sign Language Translation Transformer | |
| SMA* | Simplified Memory-bounded A* Search Algorithm | |
| SMBO | Sequential Model-Based Optimization | |
| SMO | Sequential Minimal Optimization | |
| SMOTE | Synthetic Minority Over-sampling Technique | |
| SNN | Sparse Neural Network | |
| SOM | Self-Organizing Map | |
| SOTA | State of the Art | |
| SPARQL | SPARQL Protocol and RDF Query Language | |
| Spiking NN | Spiking Neural Network | |
| SPM | SentencePiece Model (subword tokenization) | |
| SpRay | Spectral Relevance Analysis | |
| SSD | Single-Shot Detector | |
| SSL | Self-Supervised Learning | |
| SSVM | Smooth support vector machine | |
| ST | Style transfer | |
| STaR | Self-Taught Reasoner | |
| STDA | Style Transfer Data Augmentation | |
| STDP | Spike Timing-Dependent Plasticity | |
| STL | Selt-Taught Learning | |
| SUMO | Simulation of Urban Mobility | |
| SURF | Speeded-Up Robust Features (feature detection) | |
| SVC | Support Vector Classification | |
| SVD | Singing Voice Detection | |
| SVM | Support vector machine | |
| SVR | Support Vector Regression | |
| SVS | Singing Voice Separation | |
| SWI-Prolog | Semantic Web Interface for Prolog | |
| t-SNE | t-distributed stochastic neighbor embedding | |
| T5 | Text-To-Text Transfer Transformer | |
| TD | Temporal Difference | |
| TDA | Targeted Data Augmentation | |
| TDE | Time Domain Ensemble | |
| tf-idf | term frequency-inverse document frequency | |
| TGAN | Temporal Generative Adversarial Network | |
| THAID | THeta Automatic Interaction Detection | |
| TINT | Tree-Interpreter | |
| TL | Transfer Learning | |
| TLFN | Time-Lagged Feedforward Neural Network | |
| TN | True negative | |
| TNR | True negative rate | |
| ToM | Theory of Mind | |
| TP | True positive | |
| TPOT | Tree-based Pipeline Optimization Tool | |
| TPR | True positive rate | |
| TPU | Tensor Processing Unit | |
| TRPO | Trust Region Policy Optimization | |
| TS | Tabu Search | |
| TSF | Time Series Forest | |
| TSP | Traveling Salesman Problem | |
| TTS | Text-to-Speech | |
| UCT | Upper Confidence bounds applied to Trees (Monte Carlo Tree Search variant) | |
| UDA | Unsupervised Data Augmentation | |
| UKF | Unscented Kalman Filter | |
| UL | Unsupervised learning | |
| ULMFiT | Universal Language Model Fine-Tuning | |
| UMAP | Uniform Manifold Approximation and Projection | |
| USM | Universal Speech Model | |
| V-Net | Volumetric Convolutional neural network | |
| VAD | Voice Activity Detection | |
| VAE | Variational AutoEncoder | |
| VGG | Visual Geometry Group | |
| VHRED | Variational Hierarchical Recurrent Encoder-Decoder | |
| VISSIM | A traffic simulation software (from "Verkehr In Städten | |
| ViT | Vision Transformer | |
| VLM | Vision-Language Model | |
| VPNN | Vector Product Neural Network | |
| VQ-VAE | Vector Quantized Variational Autoencoders | |
| VQE | Variational Quantum Eigensolver | |
| VR | Virtual reality | |
| VRP | Vehicle Routing Problem | |
| VUI | Voice User Interface | |
| WCSP | Weighted Constraint Satisfaction Problem | |
| WER | Word Error Rate | |
| WFST | Weighted finite-state transducer (WFST) | |
| WGAN | Wasserstein Generative Adversarial Network | |
| WMA | Weighted Majority Algorithm | |
| WPE | Weighted Prediction Error | |
| XAI | Explainable Artificial Intelligence | |
| XGBoost | eXtreme Gradient Boosting | |
| XOR | Exclusive OR (a common problem in neural networks) | |
| YOLO | You Only Look Once | |
| ZSL | Zero-Shot Learning |
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