| 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
|
| 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
|
| MMI |
|
Maximum Mutual Information
|
| MNIST |
|
Modified National Institute of Standards and Technology
|
| MOEA |
|
Multi-Objective Evolutionary Algorithm
|
| 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
|
| 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 |
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Rectified Linear Unit
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| REPTree |
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Reduced Error Pruning Tree
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| RETRO |
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Retrieval Enhanced Transformer
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| RF |
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Random forest
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| RFE |
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Recursive Feature Elimination
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| RGB |
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Red Green Blue color model
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| RICNN |
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Rotation Invariant Convolutional Neural Network
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| RIM |
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Recurrent Interence Machines
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| RIPPER |
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Repeated Incremental Pruning to Produce Error Reduction
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| RISE |
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Random Interval Spectral Ensemble
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| RL |
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Reinforcement learning
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| RLFM |
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Regression based latent factors
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| RLHF |
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Reinforcement Learning from Human Feedback
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| RMSE |
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Root mean squared error
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| RMSLE |
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Root mean squared logarithmic error
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| RMSprop |
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Root Mean Square Propagation
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| RNN |
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Recurrent neural network
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| RNNLM |
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Recurrent Neural Network Language Model (RNNLM)
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| RoBERTa |
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Robustly Optimized BERT Pretraining Approach
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| ROC |
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Receiver operating characteristic
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| ROI |
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Region Of Interest
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| ROS |
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Robot Operating System
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| ROUGE |
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Recall-Oriented Understudy for Gisting Evaluation (NLP metric)
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| RPA |
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Robotic Process Automation
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| RR |
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Ridge Regression
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| RRT |
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Rapidly-exploring Random Tree (motion planning algorithm)
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| RSI |
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Recursive self-improvement
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| RTRL |
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Real-Time Recurrent Learning
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| SA |
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Simulated Annealing, Segment Anything
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| SAM |
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Segment Anything Model
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| SaaS |
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Software as a Service
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| SAC |
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Soft Actor-Critic
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| SAE |
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Stacked AE
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| SARSA |
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State-Action-Reward-State-Action
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| SAT |
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Satisfiability Problem
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| SBAC |
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Situation-Based Access Control
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| SBM |
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Stochastic block model
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| SBO |
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Structured Bayesian optimization
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| SBSE |
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Search-based software engineering
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| SCH |
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Stochastic convex hull
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| SCIP |
|
Solving Constraint Integer Programs
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| SDAE |
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Stacked DAE
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| seq2seq |
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Sequence to Sequence Learning
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| SER |
|
Sentence Error Rate
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| SGBoost |
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Stochastic Gradient Boosting
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| SGD |
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Stochastic gradient descent
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| SGVB |
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Stochastic Gradient Variational Bayes
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| SHAP |
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SHapley Additive exPlanation
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| SHLLE |
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Supervised Hessian Locally Linear Embedding
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| SIFT |
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Scale-Invariant Feature Transform (feature detection)
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| Sign2(Gloss+Text) |
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Sign to Gloss and Text
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| Sign2Gloss |
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A one to one translation from the single sign to the single gloss.
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| Sign2Text |
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A task of full translation from the sign language into the spoken one
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| SL |
|
Supervised learning
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| SLAM |
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Simultaneous Localization and Mapping
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| SLDS |
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Switching Linear Dynamical System
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| SLP |
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Single-Layer Perceptron
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| SLRT |
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Sign Language Recognition Transformer
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| SLT |
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Sign Language Translation
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| SLTT |
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Sign Language Translation Transformer
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| SMA* |
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Simplified Memory-bounded A* Search Algorithm
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| SMBO |
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Sequential Model-Based Optimization
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| SMO |
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Sequential Minimal Optimization
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| SMOTE |
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Synthetic Minority Over-sampling Technique
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| SNN |
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Sparse Neural Network
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| SOM |
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Self-Organizing Map
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| SOTA |
|
State of the Art
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| SPARQL |
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SPARQL Protocol and RDF Query Language
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| Spiking NN |
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Spiking Neural Network
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| SPM |
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SentencePiece Model (subword tokenization)
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| SpRay |
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Spectral Relevance Analysis
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| SSD |
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Single-Shot Detector
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| SSL |
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Self-Supervised Learning
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| SSVM |
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Smooth support vector machine
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| ST |
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Style transfer
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| STaR |
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Self-Taught Reasoner
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| STDA |
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Style Transfer Data Augmentation
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| STDP |
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Spike Timing-Dependent Plasticity
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| STL |
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Selt-Taught Learning
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| SUMO |
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Simulation of Urban Mobility
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| SURF |
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Speeded-Up Robust Features (feature detection)
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| SVC |
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Support Vector Classification
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| SVD |
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Singing Voice Detection
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| SVM |
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Support vector machine
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| SVR |
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Support Vector Regression
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| SVS |
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Singing Voice Separation
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| SWI-Prolog |
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Semantic Web Interface for Prolog
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| t-SNE |
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t-distributed stochastic neighbor embedding
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| T5 |
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Text-To-Text Transfer Transformer
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| TD |
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Temporal Difference
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| TDA |
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Targeted Data Augmentation
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| TDE |
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Time Domain Ensemble
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| tf-idf |
|
term frequency–inverse document frequency
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| TGAN |
|
Temporal Generative Adversarial Network
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| THAID |
|
THeta Automatic Interaction Detection
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| TINT |
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Tree-Interpreter
|
| TL |
|
Transfer Learning
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| TLFN |
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Time-Lagged Feedforward Neural Network
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| TN |
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True negative
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| TNR |
|
True negative rate
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| ToM |
|
Theory of Mind
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| TP |
|
True positive
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| TPOT |
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Tree-based Pipeline Optimization Tool
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| TPR |
|
True positive rate
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| TPU |
|
Tensor Processing Unit
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| TRPO |
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Trust Region Policy Optimization
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| TS |
|
Tabu Search
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| TSF |
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Time Series Forest
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| TSP |
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Traveling Salesman Problem
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| TTS |
|
Text-to-Speech
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| UCT |
|
Upper Confidence bounds applied to Trees (Monte Carlo Tree Search variant)
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| UDA |
|
Unsupervised Data Augmentation
|
| UKF |
|
Unscented Kalman Filter
|
| UL |
|
Unsupervised learning
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| ULMFiT |
|
Universal Language Model Fine-Tuning
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| UMAP |
|
Uniform Manifold Approximation and Projection
|
| USM |
|
Universal Speech Model
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| V-Net |
|
Volumetric Convolutional neural network
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| VAD |
|
Voice Activity Detection
|
| VAE |
|
Variational AutoEncoder
|
| VGG |
|
Visual Geometry Group
|
| VHRED |
|
Variational Hierarchical Recurrent Encoder-Decoder
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| VISSIM |
|
A traffic simulation software (from "Verkehr In Städten
|
| ViT |
|
Vision Transformer
|
| 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)
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| WGAN |
|
Wasserstein Generative Adversarial Network
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| 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
|