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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)

Approximate Marginals in Latent Gaussian Models JMLR 2011 Approximate Model Selection for Large Scale LSSVM ACML 2011 Approximating Semidefinite Programs in Sublinear Time 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 Serial Approach to Handling High-Dimensional Measurements in the Sigma-Point Kalman Filter RSS 2011 A simple multi-armed bandit algorithm with optimal variation-bounded regret COLT 2011 A Spike and Slab Restricted Boltzmann Machine AISTATS 2011 Asymptotic Theory for Linear-Chain Conditional Random Fields AISTATS 2011 A Two-Stage Weighting Framework for Multi-Source Domain Adaptation NeurIPS 2011 Automated Refinement of Bayes Networks' Parameters based on Test Ordering Constraints NeurIPS 2011 Automatic Calibration of Multiple Coplanar Sensors RSS 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 Bayesian Generalized Kernel Mixed Models JMLR 2011 Bayesian Hierarchical Cross-Clustering AISTATS 2011 Bayesian Inference for Statistical Abduction Using Markov Chain Monte Carlo ACML 2011 Bayesian Partitioning of Large-Scale Distance Data NeurIPS 2011 Bayesian Spike-Triggered Covariance Analysis NeurIPS 2011 Beating SGD: Learning SVMs in Sublinear Time NeurIPS 2011 Better Algorithms for Benign Bandits JMLR 2011