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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

1
20
220
477
4,652
9,258
2000
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Papers (including subtopics)

Online Learning: Random Averages, Combinatorial Parameters, and Learnability NeurIPS 2010 Online Markov Decision Processes under Bandit Feedback NeurIPS 2010 Online Passive-Aggressive Algorithms on a Budget AISTATS 2010 On the Convexity of Latent Social Network Inference NeurIPS 2010 On the Foundations of Noise-free Selective Classification JMLR 2010 On the Theory of Learnining with Privileged Information NeurIPS 2010 PAC-Bayesian Model Selection for Reinforcement Learning NeurIPS 2010 Parametric Bandits: The Generalized Linear Case NeurIPS 2010 Parametric Herding AISTATS 2010 PLISS: Detecting and Labeling Places Using Online Change-Point Detection RSS 2010 Policy gradients in linearly-solvable MDPs NeurIPS 2010 Posterior Regularization for Structured Latent Variable Models JMLR 2010 Practical Large-Scale Optimization for Max-norm Regularization NeurIPS 2010 Predicting Execution Time of Computer Programs Using Sparse Polynomial Regression NeurIPS 2010 Predictive State Temporal Difference Learning NeurIPS 2010 Predictive Subspace Learning for Multi-view Data: a Large Margin Approach NeurIPS 2010 Probabilistic latent variable models for distinguishing between cause and effect NeurIPS 2010 Probabilistic Multi-Task Feature Selection NeurIPS 2010 Rademacher Complexities and Bounding the Excess Risk in Active Learning JMLR 2010 Random Walk Approach to Regret Minimization NeurIPS 2010 Rates of convergence for the cluster tree NeurIPS 2010 Reduced-Rank Hidden Markov Models AISTATS 2010 Reducing Label Complexity by Learning From Bags AISTATS 2010 Regret Bounds for Gaussian Process Bandit Problems AISTATS 2010 Regularized estimation of image statistics by Score Matching NeurIPS 2010