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Learning Types

56,253 papers (3 classified directly here)

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)
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Papers (including subtopics)

PropBank-Powered Data Creation: Utilizing Sense-Role Labelling to Generate Disaster Scenario Data COLING 2024 Propensity Score Alignment of Unpaired Multimodal Data NeurIPS 2024 Proportional Aggregation of Preferences for Sequential Decision Making AAAI 2024 ProS: Facial Omni-Representation Learning via Prototype-Based Self-Distillation WACV 2024 Prospective Learning: Learning for a Dynamic Future NeurIPS 2024 Prospective Representation Learning for Non-Exemplar Class-Incremental Learning NeurIPS 2024 Prospector: Improving LLM Agents with Self-Asking and Trajectory Ranking EMNLP 2024 ProSST: Protein Language Modeling with Quantized Structure and Disentangled Attention NeurIPS 2024 Prot2Text: Multimodal Protein’s Function Generation with GNNs and Transformers AAAI 2024 Protected Test-Time Adaptation via Online Entropy Matching: A Betting Approach NeurIPS 2024 Protein-ligand binding representation learning from fine-grained interactions ICLR 2024 Protein-Nucleic Acid Complex Modeling with Frame Averaging Transformer NeurIPS 2024 ProtLLM: An Interleaved Protein-Language LLM with Protein-as-Word Pre-Training ACL 2024 Prototypical Contrastive Network for Imbalanced Aerial Image Segmentation WACV 2024 Prototypical Reward Network for Data-Efficient RLHF ACL 2024 Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo ICLR 2024 Provable Benefits of Multi-task RL under Non-Markovian Decision Making Processes ICLR 2024 Provable Compositional Generalization for Object-Centric Learning ICLR 2024 Provable Contrastive Continual Learning ICML 2024 Provable Interactive Learning with Hindsight Instruction Feedback ICML 2024 Provable Memory Efficient Self-Play Algorithm for Model-free Reinforcement Learning ICLR 2024 Provable Offline Preference-Based Reinforcement Learning ICLR 2024 Provable Partially Observable Reinforcement Learning with Privileged Information NeurIPS 2024 Provable Policy Gradient Methods for Average-Reward Markov Potential Games AISTATS 2024 Provable Robustness against a Union of L_0 Adversarial Attacks AAAI 2024