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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)

Streaming k-means approximation NeurIPS 2009 Strong Limit Theorems for the Bayesian Scoring Criterion in Bayesian Networks JMLR 2009 Subgroup Analysis via Recursive Partitioning JMLR 2009 Submanifold density estimation NeurIPS 2009 Submodularity Cuts and Applications NeurIPS 2009 Sufficient Conditions for Agnostic Active Learnable NeurIPS 2009 The Infinite Partially Observable Markov Decision Process NeurIPS 2009 The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs JMLR 2009 The P-Norm Push: A Simple Convex Ranking Algorithm that Concentrates at the Top of the List JMLR 2009 The Wisdom of Crowds in the Recollection of Order Information NeurIPS 2009 Thresholding Procedures for High Dimensional Variable Selection and Statistical Estimation NeurIPS 2009 Time-extended multi-robot coordination for domains with intra-path constraints RSS 2009 Time-rescaling methods for the estimation and assessment of non-Poisson neural encoding models NeurIPS 2009 Time-Varying Dynamic Bayesian Networks NeurIPS 2009 Toward Provably Correct Feature Selection in Arbitrary Domains NeurIPS 2009 Tracking Dynamic Sources of Malicious Activity at Internet Scale NeurIPS 2009 Training Factor Graphs with Reinforcement Learning for Efficient MAP Inference NeurIPS 2009 Ultrahigh Dimensional Feature Selection: Beyond The Linear Model JMLR 2009 Universal Kernel-Based Learning with Applications to Regular Languages JMLR 2009 Unsupervised Feature Selection for the k-means Clustering Problem NeurIPS 2009 Using the distribution theory to simultaneously calibrate the sensors of a mobile robot RSS 2009 Variational Inference for the Nested Chinese Restaurant Process NeurIPS 2009 When Is There a Representer Theorem? Vector Versus Matrix Regularizers JMLR 2009 Which graphical models are difficult to learn? NeurIPS 2009 Whose Vote Should Count More: Optimal Integration of Labels from Labelers of Unknown Expertise NeurIPS 2009