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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)

A rational decision making framework for inhibitory control NeurIPS 2010 A Reduction from Apprenticeship Learning to Classification NeurIPS 2010 A Regularization Approach to Nonlinear Variable Selection AISTATS 2010 A Rotation Test to Verify Latent Structure JMLR 2010 A Streaming Parallel Decision Tree Algorithm JMLR 2010 Asymptotic Equivalence of Bayes Cross Validation and Widely Applicable Information Criterion in Singular Learning Theory JMLR 2010 A Theory of Multiclass Boosting NeurIPS 2010 Auto-Regressive HMM Inference with Incomplete Data for Short-Horizon Wind Forecasting NeurIPS 2010 Avoiding False Positive in Multi-Instance Learning NeurIPS 2010 Basis Construction from Power Series Expansions of Value Functions NeurIPS 2010 Batch Bayesian Optimization via Simulation Matching NeurIPS 2010 Bayesian Gaussian Process Latent Variable Model AISTATS 2010 Bayesian Generalized Kernel Models AISTATS 2010 Bayesian Learning in Sparse Graphical Factor Models via Variational Mean-Field Annealing JMLR 2010 Bayesian Online Learning for Multi-label and Multi-variate Performance Measures AISTATS 2010 Bayesian structure discovery in Bayesian networks with less space AISTATS 2010 Bayesian variable order Markov models AISTATS 2010 b-Bit Minwise Hashing for Estimating Three-Way Similarities NeurIPS 2010 Belief space planning assuming maximum likelihood observations RSS 2010 Block Variable Selection in Multivariate Regression and High-dimensional Causal Inference NeurIPS 2010 Boosted Optimization for Network Classification AISTATS 2010 Boosting Classifier Cascades NeurIPS 2010 Bundle Methods for Regularized Risk Minimization JMLR 2010 Categories and Functional Units: An Infinite Hierarchical Model for Brain Activations NeurIPS 2010 Chromatic PAC-Bayes Bounds for Non-IID Data: Applications to Ranking and Stationary β-Mixing Processes JMLR 2010