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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)

Lifted Inference Seen from the Other Side : The Tractable Features NeurIPS 2010 Linear Algorithms for Online Multitask Classification JMLR 2010 Linear Complementarity for Regularized Policy Evaluation and Improvement NeurIPS 2010 Linear readout from a neural population with partial correlation data NeurIPS 2010 Lower Bounds on Rate of Convergence of Cutting Plane Methods NeurIPS 2010 LSTD with Random Projections NeurIPS 2010 MAP Estimation for Graphical Models by Likelihood Maximization NeurIPS 2010 MAP estimation in Binary MRFs via Bipartite Multi-cuts NeurIPS 2010 Mass Fatality Incident Identification based on nuclear DNA evidence AISTATS 2010 Maximum Likelihood in Cost-Sensitive Learning: Model Specification, Approximations, and Upper Bounds JMLR 2010 Maximum Relative Margin and Data-Dependent Regularization JMLR 2010 Mean Field Variational Approximation for Continuous-Time Bayesian Networks JMLR 2010 Minimum Conditional Entropy Clustering: A Discriminative Framework for Clustering ACML 2010 Mixture of time-warped trajectory models for movement decoding NeurIPS 2010 Model-based Boosting 2.0 JMLR 2010 Model Selection: Beyond the Bayesian/Frequentist Divide JMLR 2010 Moreau-Yosida Regularization for Grouped Tree Structure Learning NeurIPS 2010 Multi-label Multiple Kernel Learning by Stochastic Approximation: Application to Visual Object Recognition NeurIPS 2010 Multiple Kernel Learning and the SMO Algorithm NeurIPS 2010 Multi-Priority Cartesian Impedance Control RSS 2010 Multi-Stage Dantzig Selector NeurIPS 2010 Multi-Task Learning using Generalized t Process AISTATS 2010 Multivariate Dyadic Regression Trees for Sparse Learning Problems NeurIPS 2010 Multi-View Active Learning in the Non-Realizable Case NeurIPS 2010 Natural Policy Gradient Methods with Parameter-based Exploration for Control Tasks NeurIPS 2010