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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)

Distribution Learning with Valid Outputs Beyond the Worst-Case NeurIPS 2024 Distribution Matching for Multi-Task Learning of Classification Tasks: A Large-Scale Study on Faces & Beyond AAAI 2024 Dive into the Chasm: Probing the Gap between In- and Cross-Topic Generalization EACL 2024 Diverse and Effective Synthetic Data Generation for Adaptable Zero-Shot Dialogue State Tracking EMNLP 2024 Diverse Imagenet Models Transfer Better WACV 2024 Diverse Yet Biased: Towards Mitigating Biases in Generative AI (Student Abstract) AAAI 2024 Diversified and Personalized Multi-rater Medical Image Segmentation CVPR 2024 Diversifying Training Pool Predictability for Zero-shot Coordination: A Theory of Mind Approach IJCAI 2024 Diversify, Rationalize, and Combine: Ensembling Multiple QA Strategies for Zero-shot Knowledge-based VQA EMNLP 2024 Diversity-Aware Annotation for Conversational AI Safety COLING 2024 Diversity Is Not All You Need: Training A Robust Cooperative Agent Needs Specialist Partners NeurIPS 2024 Diversity Over Size: On the Effect of Sample and Topic Sizes for Topic-Dependent Argument Mining Datasets EMNLP 2024 Divide-and-Aggregate Learning for Evaluating Performance on Unlabeled Data AAAI 2024 Divide-and-Conquer Meets Consensus: Unleashing the Power of Functions in Code Generation NeurIPS 2024 Divide and not forget: Ensemble of selectively trained experts in Continual Learning ICLR 2024 Diving Segmentation Model into Pixels ICLR 2024 DKEC: Domain Knowledge Enhanced Multi-Label Classification for Diagnosis Prediction EMNLP 2024 DLM: A Decoupled Learning Model for Long-tailed Polyphone Disambiguation in Mandarin NAACL 2024 DLUT and GTCOM’s Neural Machine Translation Systems for WMT24 EMNLP 2024 DM-BLI: Dynamic Multiple Subspaces Alignment for Unsupervised Bilingual Lexicon Induction ACL 2024 DMC-VB: A Benchmark for Representation Learning for Control with Visual Distractors NeurIPS 2024 DMMR: Cross-Subject Domain Generalization for EEG-Based Emotion Recognition via Denoising Mixed Mutual Reconstruction AAAI 2024 DMoERM: Recipes of Mixture-of-Experts for Effective Reward Modeling ACL 2024 DNA-GPT: Divergent N-Gram Analysis for Training-Free Detection of GPT-Generated Text ICLR 2024 Do causal predictors generalize better to new domains? NeurIPS 2024