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Learning Types

56,253 papers (3 classified directly here)

Subtopics · a paper can sit in several, so these overlap

Self-Supervised Learning (8,965) Adversarial Learning (5,204) Unsupervised Learning (4,874) Transfer Learning (4,808) Weakly Supervised Learning (3,938) Contrastive Learning (3,748) Zero-Shot Learning (3,130) Semi-Supervised Learning (3,128) Reinforcement Learning (3,118) Multi-Task Learning (2,556) Evaluation (2,164) Continual Learning (2,107) Active Learning (1,983) Few-Shot Learning (1,840) Deep Learning (1,404) Online Learning (1,360) Multi-Armed Bandits (1,327) Multimodal Learning (1,289) Supervised Learning (986) Multi-Agent Systems (813) Uncertainty Quantification (805) Causal Inference (636) Robustness (576) Retrieval-Augmented Generation (565) Fine-Tuning (490) Ensemble Learning (482) In-Context Learning (439) Multi-Label Classification (430) Imitation Learning (387) Prompt Engineering (270) Multi-Lingual Learning (269) Distribution Shift (264) Reinforcement Learning from Human Feedback (209) Regularization (207) Exploration-Exploitation (203) Generative Models (200) Multi-Objective Optimization (185) Out-of-Distribution Detection (176) Sparse Learning (165) Sampling (150) Preference Learning (136) Offline Reinforcement Learning (130) Multi-Label Learning (128) Markov Decision Process (127) Neural Architecture Search (122) Multi-Instance Learning (121) Multi-View Learning (117) Robust Learning (110) Generative Model (110) Time Series (108) Large Language Models (104) Exploration (103) Hyperparameter Optimization (99) Machine Unlearning (95) Imbalanced Learning (93) Machine Translation (93) Multi-Class Classification (85) Differential Privacy (82) Time Series Analysis (71) Reasoning (70) Calibration (67) Structure Learning (66) Physics-Informed Learning (62) Class Imbalance (58) Model-Based RL (55) Interactive Learning (55) Multi-Domain Learning (47) Inverse Reinforcement Learning (46) Crowdsourcing (40) Off-Policy Learning (38) Label Noise (38) Noisy Label Learning (35) Offline RL (32) Attention (32) Evolutionary Algorithm (32) Decision Making (31) Policy Learning (30) Personalization (28) Low-Resource Learning (26) Collaborative Filtering (25) Self-Training (24) Sequential Modeling (24) Parameter Estimation (23) Survival Analysis (21) Machine Learning (20) Parameter-Efficient Fine-Tuning (20) Synthetic Data Generation (20) Annotation (18) Symbolic Regression (18) AutoML (16) Security (15) Multi-Source Learning (13) Distant Supervision (13) Text Generation (11) Distributional Reinforcement Learning (9) Sentiment Analysis (9) Multi-Hop Reasoning (9) Language Modeling (9) Code Generation (8) Multi-Object Tracking (8) Natural Language Inference (7) Chain-of-Thought (6) Question Answering (5)

Papers per year

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Papers (including subtopics)

State Sequence Pooling Training of Acoustic Models for Keyword Spotting Interspeech 2020 Static and Dynamic Values of Computation in MCTS UAI 2020 Statistical Efficiency of Thompson Sampling for Combinatorial Semi-Bandits NeurIPS 2020 Statistically Efficient Off-Policy Policy Gradients ICML 2020 Stay Hungry, Stay Focused: Generating Informative and Specific Questions in Information-Seeking Conversations EMNLP 2020 Steady-State Policy Synthesis in Multichain Markov Decision Processes IJCAI 2020 Stealthy and Efficient Adversarial Attacks against Deep Reinforcement Learning AAAI 2020 Steering Distortions to Preserve Classes and Neighbors in Supervised Dimensionality Reduction NeurIPS 2020 Steering Self-Supervised Feature Learning Beyond Local Pixel Statistics CVPR 2020 Stein Self-Repulsive Dynamics: Benefits From Past Samples NeurIPS 2020 Stimulating Creativity with FunLines: A Case Study of Humor Generation in Headlines ACL 2020 Stochastically Dominant Distributional Reinforcement Learning ICML 2020 Stochastic bandits with arm-dependent delays ICML 2020 Stochastic Bandits with Delay-Dependent Payoffs AISTATS 2020 Stochastic Classifiers for Unsupervised Domain Adaptation CVPR 2020 Stochastic Convolutional Recurrent Networks for Language Modeling Interspeech 2020 Stochastic Hamiltonian Gradient Methods for Smooth Games ICML 2020 Stochastic Linear Contextual Bandits with Diverse Contexts AISTATS 2020 Stochastic Loss Function AAAI 2020 Stochastic Online Learning with Probabilistic Graph Feedback AAAI 2020 Stochastic Optimization for Performative Prediction NeurIPS 2020 Stochastic Talking Face Generation Using Latent Distribution Matching Interspeech 2020 Stock Embeddings Acquired from News Articles and Price History, and an Application to Portfolio Optimization ACL 2020 Stopping criterion for active learning based on deterministic generalization bounds AISTATS 2020 Story-level Text Style Transfer: A Proposal ACL 2020