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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)

Re-thinking Data Availability Attacks Against Deep Neural Networks CVPR 2024 Rethinking Dimensional Rationale in Graph Contrastive Learning from Causal Perspective AAAI 2024 Rethinking Discount Regularization: New Interpretations, Unintended Consequences, and Solutions for Regularization in Reinforcement Learning JMLR 2024 Rethinking Evaluation Methods for Machine Unlearning EMNLP 2024 Rethinking Exploration in Reinforcement Learning with Effective Metric-Based Exploration Bonus NeurIPS 2024 Rethinking FID: Towards a Better Evaluation Metric for Image Generation CVPR 2024 Rethinking Graph Masked Autoencoders through Alignment and Uniformity AAAI 2024 Rethinking Guidance Information to Utilize Unlabeled Samples: A Label Encoding Perspective ICML 2024 Rethinking Inverse Reinforcement Learning: from Data Alignment to Task Alignment NeurIPS 2024 Rethinking Label Poisoning for GNNs: Pitfalls and Attacks ICLR 2024 Rethinking LLM Memorization through the Lens of Adversarial Compression NeurIPS 2024 Rethinking Model Ensemble in Transfer-based Adversarial Attacks ICLR 2024 Rethinking Multi-domain Generalization with A General Learning Objective CVPR 2024 Rethinking Multi-view Representation Learning via Distilled Disentangling CVPR 2024 Rethinking Negative Instances for Generative Named Entity Recognition ACL 2024 Rethinking Pragmatics in Large Language Models: Towards Open-Ended Evaluation and Preference Tuning EMNLP 2024 Rethinking Prior Information Generation with CLIP for Few-Shot Segmentation CVPR 2024 Rethinking Reverse Distillation for Multi-Modal Anomaly Detection AAAI 2024 Rethinking Robustness Assessment: Adversarial Attacks on Learning-based Quadrupedal Locomotion Controllers RSS 2024 Rethinking Robustness of Model Attributions AAAI 2024 Rethinking Score Distillation as a Bridge Between Image Distributions NeurIPS 2024 Rethinking Skill Extraction in the Job Market Domain using Large Language Models EACL 2024 Rethinking Task-Oriented Dialogue Systems: From Complex Modularity to Zero-Shot Autonomous Agent ACL 2024 Rethinking the Bounds of LLM Reasoning: Are Multi-Agent Discussions the Key? ACL 2024 Rethinking the Evaluation of In-Context Learning for LLMs EMNLP 2024