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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)

Sparse Support Recovery with Non-smooth Loss Functions NeurIPS 2016 Sparsity and Error Analysis of Empirical Feature-Based Regularization Schemes JMLR 2016 Spectral Learning of Dynamic Systems from Nonequilibrium Data NeurIPS 2016 Spectral M-estimation with Applications to Hidden Markov Models AISTATS 2016 Spectral Methods Meet EM: A Provably Optimal Algorithm for Crowdsourcing JMLR 2016 Split LBI: An Iterative Regularization Path with Structural Sparsity NeurIPS 2016 Square Root Graphical Models: Multivariate Generalizations of Univariate Exponential Families that Permit Positive Dependencies ICML 2016 Stability and Generalization in Structured Prediction JMLR 2016 Stability of Controllers for Gaussian Process Forward Models ICML 2016 Stance Classification in Rumours as a Sequential Task Exploiting the Tree Structure of Social Media Conversations COLING 2016 Starting Small - Learning with Adaptive Sample Sizes ICML 2016 Statistical-Computational Tradeoffs in Planted Problems and Submatrix Localization with a Growing Number of Clusters and Submatrices JMLR 2016 Statistical Inference for Cluster Trees NeurIPS 2016 Statistical Inference for Pairwise Graphical Models Using Score Matching NeurIPS 2016 Statistical Matching of Discrete Data by Bayesian Networks PGM 2016 Statistical Modeling of Speaker’s Voice with Temporal Co-Location for Active Voice Authentication Interspeech 2016 Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm NeurIPS 2016 Stochastically Transitive Models for Pairwise Comparisons: Statistical and Computational Issues ICML 2016 Stochastic Block BFGS: Squeezing More Curvature out of Data ICML 2016 Stochastic Discrete Clenshaw-Curtis Quadrature ICML 2016 Stochastic Gradient Geodesic MCMC Methods NeurIPS 2016 Stochastic Gradient MCMC with Stale Gradients NeurIPS 2016 Stochastic Gradient Methods for Distributionally Robust Optimization with f-divergences NeurIPS 2016 Stochastic Gradient Richardson-Romberg Markov Chain Monte Carlo NeurIPS 2016 Stochastic Neural Networks with Monotonic Activation Functions AISTATS 2016