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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)

Distance-aware Calibration for Pre-trained Language Models EMNLP 2024 Distantly Supervised Contrastive Learning for Low-Resource Scripting Language Summarization COLING 2024 Distantly-Supervised Joint Extraction with Noise-Robust Learning ACL 2024 Distilling Causal Effect of Data in Continual Few-shot Relation Learning COLING 2024 Distilling Reliable Knowledge for Instance-Dependent Partial Label Learning AAAI 2024 Distilling Robustness into Natural Language Inference Models with Domain-Targeted Augmentation ACL 2024 DistillMIKE: Editing Distillation of Massive In-Context Knowledge Editing in Large Language Models ACL 2024 DistilVPR: Cross-Modal Knowledge Distillation for Visual Place Recognition AAAI 2024 Distortion-Disentangled Contrastive Learning WACV 2024 Distraction is All You Need: Memory-Efficient Image Immunization against Diffusion-Based Image Editing CVPR 2024 Distributed Estimation on Semi-Supervised Generalized Linear Model JMLR 2024 Distributionally Robust Model-Based Offline Reinforcement Learning with Near-Optimal Sample Complexity JMLR 2024 Distributionally Robust Model-based Reinforcement Learning with Large State Spaces AISTATS 2024 Distributionally Robust Off-Dynamics Reinforcement Learning: Provable Efficiency with Linear Function Approximation AISTATS 2024 Distributionally Robust Performative Prediction NeurIPS 2024 Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithms NeurIPS 2024 Distributional Off-Policy Evaluation for Slate Recommendations AAAI 2024 Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF ICLR 2024 Distributional regression: CRPS-error bounds for model fitting, model selection and convex aggregation NeurIPS 2024 Distributional Reinforcement Learning with Regularized Wasserstein Loss NeurIPS 2024 Distributional Successor Features Enable Zero-Shot Policy Optimization NeurIPS 2024 Distribution-Aware Data Expansion with Diffusion Models NeurIPS 2024 Distribution-aware Knowledge Prototyping for Non-exemplar Lifelong Person Re-identification CVPR 2024 Distribution Guidance Network for Weakly Supervised Point Cloud Semantic Segmentation NeurIPS 2024 Distribution-Independent Cell Type Identification for Single-Cell RNA-seq Data IJCAI 2024