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

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8

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26

18

20

135

136

147

149

220

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316

526

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477

660

1,314

2,083

3,689

4,652

5,914

6,826

8,201

8,755

9,258

2,019

2000

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Papers (including subtopics)

Large Margin Multi-Task Metric Learning NeurIPS 2010 Latent Variable Models for Predicting File Dependencies in Large-Scale Software Development NeurIPS 2010 Learning Bounds for Importance Weighting NeurIPS 2010 Learning Convolutional Feature Hierarchies for Visual Recognition NeurIPS 2010 Learning Efficient Markov Networks NeurIPS 2010 Learning from Candidate Labeling Sets NeurIPS 2010 Learning From Crowds JMLR 2010 Learning from Logged Implicit Exploration Data NeurIPS 2010 Learning invariant features using the Transformed Indian Buffet Process NeurIPS 2010 Learning Multiple Tasks using Manifold Regularization NeurIPS 2010 Learning Multiple Tasks with a Sparse Matrix-Normal Penalty NeurIPS 2010 Learning sparse dynamic linear systems using stable spline kernels and exponential hyperpriors NeurIPS 2010 Learning to combine foveal glimpses with a third-order Boltzmann machine NeurIPS 2010 Learning To Count Objects in Images NeurIPS 2010 Learning via Gaussian Herding NeurIPS 2010 Learning with Blocks: Composite Likelihood and Contrastive Divergence AISTATS 2010 Linear Complementarity for Regularized Policy Evaluation and Improvement NeurIPS 2010 LSTD with Random Projections NeurIPS 2010 Mining Recurring Concept Drifts with Limited Labeled Streaming Data ACML 2010 Mixture of time-warped trajectory models for movement decoding NeurIPS 2010 MOA: Massive Online Analysis JMLR 2010 Model-Free Monte Carlo-like Policy Evaluation AISTATS 2010 Modeling annotator expertise: Learning when everybody knows a bit of something AISTATS 2010 Monte-Carlo Planning in Large POMDPs NeurIPS 2010 More data means less inference: A pseudo-max approach to structured learning NeurIPS 2010