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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)

Revisit Multimodal Meta-Learning through the Lens of Multi-Task Learning NeurIPS 2021 Revitalizing CNN Attention via Transformers in Self-Supervised Visual Representation Learning NeurIPS 2021 RevMan: Revenue-aware Multi-task Online Insurance Recommendation AAAI 2021 Reward based Hebbian Learning in Direct Feedback Alignment (Student Abstract) AAAI 2021 Reward-Biased Maximum Likelihood Estimation for Linear Stochastic Bandits AAAI 2021 Reward Biased Maximum Likelihood Estimation for Reinforcement Learning L4DC 2021 Reward-Constrained Behavior Cloning IJCAI 2021 Reward is enough for convex MDPs NeurIPS 2021 Rewards with Negative Examples for Reinforced Topic-Focused Abstractive Summarization EMNLP 2021 RFNet: Region-Aware Fusion Network for Incomplete Multi-Modal Brain Tumor Segmentation ICCV 2021 RG PA at SemEval-2021 Task 1: A Contextual Attention-based Model with RoBERTa for Lexical Complexity Prediction SemEval 2021 RICA: Evaluating Robust Inference Capabilities Based on Commonsense Axioms EMNLP 2021 Right for Better Reasons: Training Differentiable Models by Constraining their Influence Functions AAAI 2021 RIM: Reliable Influence-based Active Learning on Graphs NeurIPS 2021 RISAN: Robust instance specific deep abstention network UAI 2021 Risk-Aware Transfer in Reinforcement Learning using Successor Features NeurIPS 2021 Risk Bounds and Calibration for a Smart Predict-then-Optimize Method NeurIPS 2021 Risk Bounds for Unsupervised Cross-Domain Mapping with IPMs JMLR 2021 Risk Minimization for Zero-shot Sequence Labeling ACL 2021 Risk Minimization from Adaptively Collected Data: Guarantees for Supervised and Policy Learning NeurIPS 2021 Risk-Sensitive Reinforcement Learning with Function Approximation: A Debiasing Approach ICML 2021 River: machine learning for streaming data in Python JMLR 2021 RL for Latent MDPs: Regret Guarantees and a Lower Bound NeurIPS 2021 RMIX: Learning Risk-Sensitive Policies for Cooperative Reinforcement Learning Agents NeurIPS 2021 RMM: Reinforced Memory Management for Class-Incremental Learning NeurIPS 2021