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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)

Non-compositional Expression Generation and its Continual Learning ACL 2024 Non-contrastive sentence representations via self-supervision NAACL 2024 Non-Exchangeable Conformal Risk Control ICLR 2024 Non-exemplar Domain Incremental Object Detection via Learning Domain Bias AAAI 2024 Non-exemplar Online Class-Incremental Continual Learning via Dual-Prototype Self-Augment and Refinement AAAI 2024 Nonlinear dynamics of localization in neural receptive fields NeurIPS 2024 Non-negative Contrastive Learning ICLR 2024 Non-Neighbors Also Matter to Kriging: A New Contrastive-Prototypical Learning AISTATS 2024 Non-parametric classification via expand-and-sparsify representation NeurIPS 2024 Nonparametric Copula Models for Multivariate, Mixed, and Missing Data JMLR 2024 Nonparametric Evaluation of Noisy ICA Solutions NeurIPS 2024 Non-parametric Representation Learning with Kernels AAAI 2024 Non-Referential Functions of Language in Social Agents: The Case of Social Proximity EACL 2024 Non-Stationary Learning of Neural Networks with Automatic Soft Parameter Reset NeurIPS 2024 Non-stationary Projection-Free Online Learning with Dynamic and Adaptive Regret Guarantees AAAI 2024 NootNoot At SemEval-2024 Task 6: Hallucinations and Related Observable Overgeneration Mistakes Detection SemEval 2024 No Prior Mask: Eliminate Redundant Action for Deep Reinforcement Learning AAAI 2024 No-Regret Algorithms for Safe Bayesian Optimization with Monotonicity Constraints AISTATS 2024 No-Regret Bandit Exploration based on Soft Tree Ensemble Model NeurIPS 2024 No-Regret Learning for Fair Multi-Agent Social Welfare Optimization NeurIPS 2024 No-Regret M${}^{\natural}$-Concave Function Maximization: Stochastic Bandit Algorithms and NP-Hardness of Adversarial Full-Information Setting NeurIPS 2024 No Regularization Is Needed: Efficient and Effective Incomplete Label Distribution Learning IJCAI 2024 No Representation, No Trust: Connecting Representation, Collapse, and Trust Issues in PPO NeurIPS 2024 Normalization and effective learning rates in reinforcement learning NeurIPS 2024 Normalizing Flows for Conformal Regression UAI 2024