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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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Papers (including subtopics)

Online allocation and homogeneous partitioning for piecewise constant mean-approximation NeurIPS 2012 Online Clustering of Processes AISTATS 2012 Online L1-Dictionary Learning with Application to Novel Document Detection NeurIPS 2012 Online Learning in the Embedded Manifold of Low-rank Matrices JMLR 2012 Online Optimization with Gradual Variations COLT 2012 Online Regret Bounds for Undiscounted Continuous Reinforcement Learning NeurIPS 2012 On-line Reinforcement Learning Using Incremental Kernel-Based Stochastic Factorization NeurIPS 2012 Online Submodular Minimization JMLR 2012 Online Sum-Product Computation Over Trees NeurIPS 2012 Online-to-Confidence-Set Conversions and Application to Sparse Stochastic Bandits AISTATS 2012 On Multilabel Classification and Ranking with Partial Feedback NeurIPS 2012 On Ranking and Generalization Bounds JMLR 2012 On Stochastic Optimal Control and Reinforcement Learning by Approximate Inference RSS 2012 On the Convergence Rate of -Norm Multiple Kernel Learning JMLR 2012 On the Necessity of Irrelevant Variables JMLR 2012 On the (Non-)existence of Convex, Calibrated Surrogate Losses for Ranking NeurIPS 2012 On the Sample Complexity of Robust PCA NeurIPS 2012 On the Structure of Nonlinearities in Pose Graph SLAM RSS 2012 On the Use of Non-Stationary Policies for Stationary Infinite-Horizon Markov Decision Processes NeurIPS 2012 Open Problem: Better Bounds for Online Logistic Regression COLT 2012 Open Problem: Does AdaBoost Always Cycle? COLT 2012 Open Problem: Is Averaging Needed for Strongly Convex Stochastic Gradient Descent? COLT 2012 Optimal Distributed Online Prediction Using Mini-Batches JMLR 2012 Optimal kernel choice for large-scale two-sample tests NeurIPS 2012 Optimal Neural Tuning Curves for Arbitrary Stimulus Distributions: Discrimax, Infomax and Minimum L_p Loss NeurIPS 2012