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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)

Internal and external pressures on language emergence: least effort, object constancy and frequency EMNLP 2020 Interpretable and Personalized Apprenticeship Scheduling: Learning Interpretable Scheduling Policies from Heterogeneous User Demonstrations NeurIPS 2020 Interpretable, Multidimensional, Multimodal Anomaly Detection with Negative Sampling for Detection of Device Failure ICML 2020 Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions ICML 2020 Interpretable Operational Risk Classification with Semi-Supervised Variational Autoencoder ACL 2020 Interpretations are Useful: Penalizing Explanations to Align Neural Networks with Prior Knowledge ICML 2020 Interpreting and Predicting Tactile Signals via a Physics-Based and Data-Driven Framework RSS 2020 Interpreting Robust Optimization via Adversarial Influence Functions ICML 2020 Inter-Task Association Critic for Cross-Resolution Person Re-Identification CVPR 2020 Intra- and Inter-Action Understanding via Temporal Action Parsing CVPR 2020 Intra-Class Variation Reduction of Speaker Representation in Disentanglement Framework Interspeech 2020 Intra-/Inter-Interaction Network with Latent Interaction Modeling for Multi-turn Response Selection COLING 2020 Intriguing Properties of Adversarial Training at Scale ICLR 2020 Intrinsically Motivated Discovery of Diverse Patterns in Self-Organizing Systems ICLR 2020 Intrinsic Evaluation of Summarization Datasets EMNLP 2020 Intrinsic Reward Driven Imitation Learning via Generative Model ICML 2020 Introducing Probabilistic Bézier Curves for N-Step Sequence Prediction AAAI 2020 Invariant Causal Prediction for Block MDPs ICML 2020 Invariant Representations through Adversarial Forgetting AAAI 2020 Invariant Risk Minimization Games ICML 2020 Inverse Learning of Symmetries NeurIPS 2020 Inverse Reinforcement Learning for Team Sports: Valuing Actions and Players IJCAI 2020 Inverting the Pose Forecasting Pipeline with SPF2: Sequential Pointcloud Forecasting for Sequential Pose Forecasting CoRL 2020 Investigating Catastrophic Forgetting During Continual Training for Neural Machine Translation COLING 2020 Investigating Learning Dynamics of BERT Fine-Tuning AACL 2020