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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)

On Mesa-Optimization in Autoregressively Trained Transformers: Emergence and Capability NeurIPS 2024 On Parameter Estimation in Deviated Gaussian Mixture of Experts AISTATS 2024 On Representation Complexity of Model-based and Model-free Reinforcement Learning ICLR 2024 On Scaling Up a Multilingual Vision and Language Model CVPR 2024 On Sensitivity of Learning with Limited Labelled Data to the Effects of Randomness: Impact of Interactions and Systematic Choices EMNLP 2024 On Softmax Direct Preference Optimization for Recommendation NeurIPS 2024 On task-relevant loss functions in meta-reinforcement learning L4DC 2024 On the Actionability of Outcome Prediction AAAI 2024 On the Adversarial Robustness of Benjamini Hochberg NeurIPS 2024 On the Benefits of Public Representations for Private Transfer Learning under Distribution Shift NeurIPS 2024 On the Comparison between Multi-modal and Single-modal Contrastive Learning NeurIPS 2024 On the Complexity of Teaching a Family of Linear Behavior Cloning Learners NeurIPS 2024 On the Computability of Robust PAC Learning COLT 2024 On the Computational Complexity of Private High-dimensional Model Selection NeurIPS 2024 On the Computational Landscape of Replicable Learning NeurIPS 2024 On the connection between Noise-Contrastive Estimation and Contrastive Divergence AISTATS 2024 On the Content Bias in Frechet Video Distance CVPR 2024 On the Convergence of an Adaptive Momentum Method for Adversarial Attacks AAAI 2024 On the Convergence of Loss and Uncertainty-based Active Learning Algorithms NeurIPS 2024 On the Distance from Calibration in Sequential Prediction COLT 2024 On the Diversity and Realism of Distilled Dataset: An Efficient Dataset Distillation Paradigm CVPR 2024 On the Duality Between Sharpness-Aware Minimization and Adversarial Training ICML 2024 On the Effectiveness of Adversarial Robustness for Abuse Mitigation with Counterspeech NAACL 2024 On the Effect of Batch Size in Byzantine-Robust Distributed Learning ICLR 2024 On the Effects of Data Scale on UI Control Agents NeurIPS 2024