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Optimization & Theory

43,292 papers (3 classified directly here)

Subtopics · a paper can sit in several, so these overlap

Optimization (17,731) Learning Theory (6,809) Bayesian Inference (6,267) Theory (5,579) Statistical Learning (4,564) Neural Network Optimization (4,155) Stochastic Processes (2,948) Stochastic Methods (1,283) Loss Functions (1,220) Distributed Learning (1,202) Online Algorithms (1,013) Statistics (822) Generalization (376) Information Theory (370) Sample Complexity (282) Sparse Optimization (241) Game Theory (151) Convex Optimization (132) Optimal Transport (104) Robust Optimization (84) Distributed Optimization (73) Approximation Algorithms (33)

Papers per year

1
52
352
828
3,646
5,854
2000
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'25

Papers (including subtopics)

Near-Optimal Bayesian Active Learning with Noisy Observations NeurIPS 2010 Near-optimal Regret Bounds for Reinforcement Learning JMLR 2010 Negative Results for Active Learning with Convex Losses AISTATS 2010 Network Flow Algorithms for Structured Sparsity NeurIPS 2010 New Adaptive Algorithms for Online Classification NeurIPS 2010 Nonlinear functional regression: a functional RKHS approach AISTATS 2010 Nonparametric Bayesian Matrix Factorization by Power-EP AISTATS 2010 Nonparametric Density Estimation for Stochastic Optimization with an Observable State Variable NeurIPS 2010 Nonparametric prior for adaptive sparsity AISTATS 2010 Non-Stochastic Bandit Slate Problems NeurIPS 2010 Object Bank: A High-Level Image Representation for Scene Classification & Semantic Feature Sparsification NeurIPS 2010 Occlusion Detection and Motion Estimation with Convex Optimization NeurIPS 2010 On Finding Predictors for Arbitrary Families of Processes JMLR 2010 On Herding and the Perceptron Cycling Theorem NeurIPS 2010 On Learning with Integral Operators JMLR 2010 Online Classification with Specificity Constraints NeurIPS 2010 Online Learning for Matrix Factorization and Sparse Coding JMLR 2010 Online Learning in The Manifold of Low-Rank Matrices NeurIPS 2010 Online Learning: Random Averages, Combinatorial Parameters, and Learnability NeurIPS 2010 Online Markov Decision Processes under Bandit Feedback NeurIPS 2010 On Over-fitting in Model Selection and Subsequent Selection Bias in Performance Evaluation JMLR 2010 On the Convergence Properties of Contrastive Divergence AISTATS 2010 On the Convexity of Latent Social Network Inference NeurIPS 2010 On the Impact of Kernel Approximation on Learning Accuracy AISTATS 2010 On the Rate of Convergence of the Bagged Nearest Neighbor Estimate JMLR 2010