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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26

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135

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149

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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)

An Analysis of Single-Layer Networks in Unsupervised Feature Learning AISTATS 2011 Anechoic Blind Source Separation Using Wigner Marginals JMLR 2011 An Empirical Evaluation of Thompson Sampling NeurIPS 2011 An Exact Algorithm for F-Measure Maximization NeurIPS 2011 A Non-Parametric Approach to Dynamic Programming NeurIPS 2011 An Unsupervised Decontamination Procedure For Improving The Reliability Of Human Judgments NeurIPS 2011 A rational model of causal inference with continuous causes NeurIPS 2011 A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning AISTATS 2011 A Refined Margin Analysis for Boosting Algorithms via Equilibrium Margin JMLR 2011 A Reinforcement Learning Theory for Homeostatic Regulation NeurIPS 2011 A reinterpretation of the policy oscillation phenomenon in approximate policy iteration NeurIPS 2011 A simple multi-armed bandit algorithm with optimal variation-bounded regret COLT 2011 Assisting Main Task Learning by Heterogeneous Auxiliary Tasks with Applications to Skin Cancer Screening AISTATS 2011 A Two-Stage Weighting Framework for Multi-Source Domain Adaptation NeurIPS 2011 Autonomous Learning of Action Models for Planning NeurIPS 2011 Bagged Structure Learning of Bayesian Network AISTATS 2011 Bandits, Query Learning, and the Haystack Dimension COLT 2011 Bayesian Bias Mitigation for Crowdsourcing NeurIPS 2011 Bayesian Co-Training JMLR 2011 Beyond the regret minimization barrier: an optimal algorithm for stochastic strongly-convex optimization COLT 2011 Blackwell Approachability and No-Regret Learning are Equivalent COLT 2011 Blending Autonomous Exploration and Apprenticeship Learning NeurIPS 2011 Boosting with Maximum Adaptive Sampling NeurIPS 2011 Bounds on Individual Risk for Log-loss Predictors COLT 2011 Budgeted Optimization with Concurrent Stochastic-Duration Experiments NeurIPS 2011