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

On Testing of Samplers NeurIPS 2020 On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Models AAAI 2020 On the Choice of Auxiliary Languages for Improved Sequence Tagging ACL 2020 On the consistency of graph-based Bayesian semi-supervised learning and the scalability of sampling algorithms JMLR 2020 On the Convergence of Model Free Learning in Mean Field Games AAAI 2020 On the design of consequential ranking algorithms UAI 2020 On the diminishing return of labeling clinical reports EMNLP 2020 On the Encoder-Decoder Incompatibility in Variational Text Modeling and Beyond ACL 2020 On the Ergodicity, Bias and Asymptotic Normality of Randomized Midpoint Sampling Method NeurIPS 2020 On The Evaluation of Machine Translation Systems Trained With Back-Translation ACL 2020 On-The-Fly Information Retrieval Augmentation for Language Models ACL 2020 On the Generalization Benefit of Noise in Stochastic Gradient Descent ICML 2020 On the Importance of Adaptive Data Collection for Extremely Imbalanced Pairwise Tasks EMNLP 2020 On the Inference Calibration of Neural Machine Translation ACL 2020 On the interaction between supervision and self-play in emergent communication ICLR 2020 On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them NeurIPS 2020 On the Optimal Weighted ℓ_2 Regularization in Overparameterized Linear Regression NeurIPS 2020 On the Robustness of Data-Driven Controllers for Linear Systems L4DC 2020 On the Robustness of Language Encoders against Grammatical Errors ACL 2020 On the Role of Sparsity and DAG Constraints for Learning Linear DAGs NeurIPS 2020 On the Role of Weight Sharing During Deep Option Learning AAAI 2020 On the Same Page? Comparing Inter-Annotator Agreement in Sentence and Document Level Human Machine Translation Evaluation EMNLP 2020 On the Sample Complexity of Adversarial Multi-Source PAC Learning ICML 2020 On the "steerability" of generative adversarial networks ICLR 2020 On the Theory of Transfer Learning: The Importance of Task Diversity NeurIPS 2020