Skip to content
conftrace_

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
'5
'10
'15
'20
'25

Papers (including subtopics)

The Value of Labeled and Unlabeled Examples when the Model is Imperfect NeurIPS 2007 Topmoumoute Online Natural Gradient Algorithm NeurIPS 2007 Transfer Learning using Kolmogorov Complexity: Basic Theory and Empirical Evaluations NeurIPS 2007 Ultrafast Monte Carlo for Statistical Summations NeurIPS 2007 Unconstrained On-line Handwriting Recognition with Recurrent Neural Networks NeurIPS 2007 Unsupervised Feature Selection for Accurate Recommendation of High-Dimensional Image Data NeurIPS 2007 Using Deep Belief Nets to Learn Covariance Kernels for Gaussian Processes NeurIPS 2007 What makes some POMDP problems easy to approximate? NeurIPS 2007 Active learning for misspecified generalized linear models NeurIPS 2006 Active Learning in Approximately Linear Regression Based on Conditional Expectation of Generalization Error JMLR 2006 Active Learning with Feedback on Features and Instances JMLR 2006 A Humanlike Predictor of Facial Attractiveness NeurIPS 2006 A Kernel Method for the Two-Sample-Problem NeurIPS 2006 A Kernel Subspace Method by Stochastic Realization for Learning Nonlinear Dynamical Systems NeurIPS 2006 A Local Learning Approach for Clustering NeurIPS 2006 An Application of Reinforcement Learning to Aerobatic Helicopter Flight NeurIPS 2006 An Approach to Bounded Rationality NeurIPS 2006 An Efficient Method for Gradient-Based Adaptation of Hyperparameters in SVM Models NeurIPS 2006 An EM Algorithm for Localizing Multiple Sound Sources in Reverberant Environments NeurIPS 2006 A Scalable Machine Learning Approach to Go NeurIPS 2006 A Switched Gaussian Process for Estimating Disparity and Segmentation in Binocular Stereo NeurIPS 2006 Attribute-efficient learning of decision lists and linear threshold functions under unconcentrated distributions NeurIPS 2006 Bayesian Detection of Infrequent Differences in Sets of Time Series with Shared Structure NeurIPS 2006 Bayesian Ensemble Learning NeurIPS 2006 Bayesian Policy Gradient Algorithms NeurIPS 2006