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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)

MaskGAN: Towards Diverse and Interactive Facial Image Manipulation CVPR 2020 Masking Orchestration: Multi-Task Pretraining for Multi-Role Dialogue Representation Learning AAAI 2020 Massively Multilingual ASR: 50 Languages, 1 Model, 1 Billion Parameters Interspeech 2020 MAST: A Memory-Augmented Self-Supervised Tracker CVPR 2020 Mastering Complex Control in MOBA Games with Deep Reinforcement Learning AAAI 2020 MAST: Multimodal Abstractive Summarization with Trimodal Hierarchical Attention EMNLP 2020 Matching Theory and Data with Personal-ITY: What a Corpus of Italian YouTube Comments Reveals About Personality COLING 2020 MATINF: A Jointly Labeled Large-Scale Dataset for Classification, Question Answering and Summarization ACL 2020 Maximizing Overall Diversity for Improved Uncertainty Estimates in Deep Ensembles AAAI 2020 Maximum-Entropy Adversarial Data Augmentation for Improved Generalization and Robustness NeurIPS 2020 Maximum Entropy Gain Exploration for Long Horizon Multi-goal Reinforcement Learning ICML 2020 Maximum Margin Multi-Dimensional Classification AAAI 2020 Maximum Nash Welfare and Other Stories About EFX IJCAI 2020 Maxmin Q-learning: Controlling the Estimation Bias of Q-learning ICLR 2020 May I Ask Who’s Calling? Named Entity Recognition on Call Center Transcripts for Privacy Law Compliance EMNLP 2020 McFlow: Monte Carlo Flow Models for Data Imputation CVPR 2020 Measurement Dependence Inducing Latent Causal Models UAI 2020 Measuring and Improving the Use of Graph Information in Graph Neural Networks ICLR 2020 Measuring and Relieving the Over-Smoothing Problem for Graph Neural Networks from the Topological View AAAI 2020 Measuring Compositional Generalization: A Comprehensive Method on Realistic Data ICLR 2020 Measuring Emotions in the COVID-19 Real World Worry Dataset ACL 2020 Measuring the Discrepancy between Conditional Distributions: Methods, Properties and Applications IJCAI 2020 Median Matrix Completion: from Embarrassment to Optimality ICML 2020 MeDIL: A Python Package for Causal Modelling PGM 2020 Meeting the 2020 Duolingo Challenge on a Shoestring ACL 2020