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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)

Infinite Latent SVM for Classification and Multi-task Learning NeurIPS 2011 Iterative Learning for Reliable Crowdsourcing Systems NeurIPS 2011 Joint 3D Estimation of Objects and Scene Layout NeurIPS 2011 k-NN Regression Adapts to Local Intrinsic Dimension NeurIPS 2011 Laplacian Support Vector Machines Trained in the Primal JMLR 2011 Large-Scale Category Structure Aware Image Categorization NeurIPS 2011 Learning a Tree of Metrics with Disjoint Visual Features NeurIPS 2011 Learning Auto-regressive Models from Sequence and Non-sequence Data NeurIPS 2011 Learning Class-relevant Features and Class-irrelevant Features via a Hybrid third-order RBM AISTATS 2011 Learning Eigenvectors for Free NeurIPS 2011 Learning from Partial Labels JMLR 2011 Learning from positive and unlabeled examples by enforcing statistical significance AISTATS 2011 Learning High-Dimensional Markov Forest Distributions: Analysis of Error Rates JMLR 2011 Learning Higher-Order Graph Structure with Features by Structure Penalty NeurIPS 2011 Learning Patient-Specific Cancer Survival Distributions as a Sequence of Dependent Regressors NeurIPS 2011 Learning Sparse Representations of High Dimensional Data on Large Scale Dictionaries NeurIPS 2011 Learning to Agglomerate Superpixel Hierarchies NeurIPS 2011 Learning to Learn with Compound HD Models NeurIPS 2011 Learning to Search Efficiently in High Dimensions NeurIPS 2011 Linear Submodular Bandits and their Application to Diversified Retrieval NeurIPS 2011 Lower Bounds for Passive and Active Learning NeurIPS 2011 Machine Learning Markets AISTATS 2011 MAP Inference for Bayesian Inverse Reinforcement Learning NeurIPS 2011 Matrix Completion for Multi-label Image Classification NeurIPS 2011 Maximum Covariance Unfolding : Manifold Learning for Bimodal Data NeurIPS 2011