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Learning Types

56,253 papers (3 classified directly here)

Subtopics · a paper can sit in several, so these overlap

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)

Papers per year

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Papers (including subtopics)

Distributional Multivariate Policy Evaluation and Exploration with the Bellman GAN ICML 2019 Distributional reinforcement learning with linear function approximation AISTATS 2019 Distributional Semantics Meets Multi-Label Learning AAAI 2019 Distribution-Based Semi-Supervised Learning for Activity Recognition AAAI 2019 Distribution Consistency Based Covariance Metric Networks for Few-Shot Learning AAAI 2019 Distribution Learning of a Random Spatial Field with a Location-Unaware Mobile Sensor NeurIPS 2019 Distribution oblivious, risk-aware algorithms for multi-armed bandits with unbounded rewards NeurIPS 2019 Divergence-Augmented Policy Optimization NeurIPS 2019 Divergence Triangle for Joint Training of Generator Model, Energy-Based Model, and Inferential Model CVPR 2019 Diverse Exploration via Conjugate Policies for Policy Gradient Methods AAAI 2019 Diversity-Driven Extensible Hierarchical Reinforcement Learning AAAI 2019 Diversity-Inducing Policy Gradient: Using Maximum Mean Discrepancy to Find a Set of Diverse Policies IJCAI 2019 Diversity is All You Need: Learning Skills without a Reward Function ICLR 2019 Diversity-Sensitive Conditional Generative Adversarial Networks ICLR 2019 Diversity With Cooperation: Ensemble Methods for Few-Shot Classification ICCV 2019 DIVINE: A Generative Adversarial Imitation Learning Framework for Knowledge Graph Reasoning EMNLP 2019 DIViS: Domain Invariant Visual Servoing for Collision-Free Goal Reaching RSS 2019 DL2: Training and Querying Neural Networks with Logic ICML 2019 DM2C: Deep Mixed-Modal Clustering NeurIPS 2019 DocRED: A Large-Scale Document-Level Relation Extraction Dataset ACL 2019 Document-Level Event Factuality Identification via Adversarial Neural Network NAACL 2019 Does Learning Specific Features for Related Parts Help Human Pose Estimation? CVPR 2019 Domain Adaptation for Person-Job Fit with Transferable Deep Global Match Network EMNLP 2019 Domain Adaptation for Semantic Segmentation With Maximum Squares Loss ICCV 2019 Domain Adaptation for Structured Output via Discriminative Patch Representations ICCV 2019