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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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20
220
477
4,652
9,258
2000
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Papers (including subtopics)

Reformulating Unsupervised Style Transfer as Paraphrase Generation EMNLP 2020 Re-framing Incremental Deep Language Models for Dialogue Processing with Multi-task Learning COLING 2020 Regional Tree Regularization for Interpretability in Deep Neural Networks AAAI 2020 Regression under Human Assistance AAAI 2020 Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information JMLR 2020 Regression with reject option and application to kNN NeurIPS 2020 Regret Analysis of Bandit Problems with Causal Background Knowledge UAI 2020 Regret Bound for Safe Gaussian Process Bandit Optimization L4DC 2020 Regret Bounds for Decentralized Learning in Cooperative Multi-Agent Dynamical Systems UAI 2020 Regret Minimisation in Multi-Armed Bandits Using Bounded Arm Memory AAAI 2020 Regularization of Distinct Strategies for Unsupervised Question Generation EMNLP 2020 Regularized Fine-Grained Meta Face Anti-Spoofing AAAI 2020 Regularized Optimal Transport is Ground Cost Adversarial ICML 2020 Regularized Training and Tight Certification for Randomized Smoothed Classifier with Provable Robustness AAAI 2020 Regularize, Expand and Compress: NonExpansive Continual Learning WACV 2020 Regularizing Black-box Models for Improved Interpretability NeurIPS 2020 Regularizing Class-Wise Predictions via Self-Knowledge Distillation CVPR 2020 Regularizing CNN Transfer Learning With Randomised Regression CVPR 2020 Regularizing Discriminative Capability of CGANs for Semi-Supervised Generative Learning CVPR 2020 Regularizing Neural Networks via Minimizing Hyperspherical Energy CVPR 2020 Regularizing Towards Permutation Invariance In Recurrent Models NeurIPS 2020 Reinforced Curriculum Learning on Pre-Trained Neural Machine Translation Models AAAI 2020 Reinforced Multi-task Approach for Multi-hop Question Generation COLING 2020 Reinforcement Learning based Control of Imitative Policies for Near-Accident Driving RSS 2020 Reinforcement Learning Based Meta-Path Discovery in Large-Scale Heterogeneous Information Networks AAAI 2020