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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)

Global seismic monitoring as probabilistic inference NeurIPS 2010 Group Sparse Coding with a Laplacian Scale Mixture Prior NeurIPS 2010 Guaranteed Rank Minimization via Singular Value Projection NeurIPS 2010 Heavy-Tailed Process Priors for Selective Shrinkage NeurIPS 2010 Hierarchical Gaussian Process Regression ACML 2010 High Dimensional Inverse Covariance Matrix Estimation via Linear Programming JMLR 2010 High-dimensional Variable Selection with Sparse Random Projections: Measurement Sparsity and Statistical Efficiency JMLR 2010 HOP-MAP: Efficient Message Passing with High Order Potentials AISTATS 2010 Hubs in Space: Popular Nearest Neighbors in High-Dimensional Data JMLR 2010 Identifying Cause and Effect on Discrete Data using Additive Noise Models AISTATS 2010 Identifying Dendritic Processing NeurIPS 2010 Identifying graph-structured activation patterns in networks NeurIPS 2010 Implicit Differentiation by Perturbation NeurIPS 2010 Implicit encoding of prior probabilities in optimal neural populations NeurIPS 2010 Impossibility Theorems for Domain Adaptation AISTATS 2010 Improvements to the Sequence Memoizer NeurIPS 2010 Improving posterior marginal approximations in latent Gaussian models AISTATS 2010 Improving the Asymptotic Performance of Markov Chain Monte-Carlo by Inserting Vortices NeurIPS 2010 Incremental Sigmoid Belief Networks for Grammar Learning JMLR 2010 Individualized ROI Optimization via Maximization of Group-wise Consistency of Structural and Functional Profiles NeurIPS 2010 Inducing Tree-Substitution Grammars JMLR 2010 Inductive Principles for Restricted Boltzmann Machine Learning AISTATS 2010 Inference and Learning in Networks of Queues AISTATS 2010 Inference with Multivariate Heavy-Tails in Linear Models NeurIPS 2010 Infinite Predictor Subspace Models for Multitask Learning AISTATS 2010