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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

1
20
220
477
4,652
9,258
2000
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Papers (including subtopics)

Interpretable Sparse High-Order Boltzmann Machines AISTATS 2014 Investigating Haze-relevant Features in A Learning Framework for Image Dehazing CVPR 2014 Iterative Neural Autoregressive Distribution Estimator NADE-k NeurIPS 2014 Joint Inference of Multiple Label Types in Large Networks ICML 2014 Just-In-Time Learning for Fast and Flexible Inference NeurIPS 2014 Large-scale Multi-label Learning with Missing Labels ICML 2014 Large-Scale Optimization of Hierarchical Features for Saliency Prediction in Natural Images CVPR 2014 Learnability of the Superset Label Learning Problem ICML 2014 Learning a Concept Hierarchy from Multi-labeled Documents NeurIPS 2014 Learning and Evaluation in Presence of Non-i.i.d. Label Noise AISTATS 2014 Learning Articulated Motions From Visual Demonstration RSS 2014 Learning-Based Atlas Selection for Multiple-Atlas Segmentation CVPR 2014 Learning-by-Synthesis for Appearance-based 3D Gaze Estimation CVPR 2014 Learning Chordal Markov Networks by Dynamic Programming NeurIPS 2014 Learning Coverage Functions and Private Release of Marginals COLT 2014 Learning Deep Features for Scene Recognition using Places Database NeurIPS 2014 Learning Everything about Anything: Webly-Supervised Visual Concept Learning CVPR 2014 Learning From Weakly Supervised Data by The Expectation Loss SVM (e-SVM) algorithm NeurIPS 2014 Learning Inhomogeneous FRAME Models for Object Patterns CVPR 2014 Learning Mixtures of Discrete Product Distributions using Spectral Decompositions COLT 2014 Learning Multiple Tasks in Parallel with a Shared Annotator NeurIPS 2014 Learning Neural Network Policies with Guided Policy Search under Unknown Dynamics NeurIPS 2014 Learning on graphs using Orthonormal Representation is Statistically Consistent NeurIPS 2014 Learning Polynomials with Neural Networks ICML 2014 Learning Shuffle Ideals Under Restricted Distributions NeurIPS 2014