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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)

Learning Factored Markov Decision Processes with Unawareness UAI 2019 LEARNING FACTORIZED REPRESENTATIONS FOR OPEN-SET DOMAIN ADAPTATION ICLR 2019 Learning Fairness in Multi-Agent Systems NeurIPS 2019 Learning Feature-to-Feature Translator by Alternating Back-Propagation for Generative Zero-Shot Learning ICCV 2019 Learning Flexible Latent Representations via Encapsulated Variational Encoders AAAI 2019 Learning for Single-Shot Confidence Calibration in Deep Neural Networks Through Stochastic Inferences CVPR 2019 Learning for Tail Label Data: A Label-Specific Feature Approach IJCAI 2019 Learning from a Learner ICML 2019 Learning from Bad Data via Generation NeurIPS 2019 Learning from brains how to regularize machines NeurIPS 2019 Learning from demonstration with model-based Gaussian process CoRL 2019 Learning from Dialogue after Deployment: Feed Yourself, Chatbot! ACL 2019 Learning from Few Subjects with Large Amounts of Voice Monitoring Data MLHC 2019 Learning from Label Proportions with Generative Adversarial Networks NeurIPS 2019 Learning From Noisy Labels by Regularized Estimation of Annotator Confusion CVPR 2019 Learning from Positive and Unlabeled Data with a Selection Bias ICLR 2019 Learning from sparsely annotated data for semantic segmentation in histopathology images MIDL 2019 Learning from the Experience of Doctors: Automated Diagnosis of Appendicitis Based on Clinical Notes ACL 2019 Learning from Trajectories via Subgoal Discovery NeurIPS 2019 Learning from Web Data Using Adversarial Discriminative Neural Networks for Fine-Grained Classification AAAI 2019 Learning Generalizable Device Placement Algorithms for Distributed Machine Learning NeurIPS 2019 Learning Generalized Temporal Abstractions across Both Action and Perception AAAI 2019 Learning Hawkes Processes from a handful of events NeurIPS 2019 Learning Hierarchical Priors in VAEs NeurIPS 2019 Learning How to Active Learn by Dreaming ACL 2019