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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)

Infinite-Dimensional Kalman Filtering Approach to Spatio-Temporal Gaussian Process Regression AISTATS 2012 Information Theoretic Model Validation for Spectral Clustering AISTATS 2012 Informative Priors for Markov Blanket Discovery AISTATS 2012 Interpreting prediction markets: a stochastic approach NeurIPS 2012 Isotropic Hashing NeurIPS 2012 Iterative ranking from pair-wise comparisons NeurIPS 2012 Iterative Reweighted Algorithms for Matrix Rank Minimization JMLR 2012 Iterative Thresholding Algorithm for Sparse Inverse Covariance Estimation NeurIPS 2012 Joint Estimation of Structured Sparsity and Output Structure in Multiple-Output Regression via Inverse-Covariance Regularization AISTATS 2012 Joint Modeling of a Matrix with Associated Text via Latent Binary Features NeurIPS 2012 Kernel Hyperalignment NeurIPS 2012 Kernels Based Tests with Non-asymptotic Bootstrap Approaches for Two-sample Problems COLT 2012 Kernel Topic Models AISTATS 2012 Krylov Subspace Descent for Deep Learning AISTATS 2012 L1 Covering Numbers for Uniformly Bounded Convex Functions COLT 2012 Large Scale Distributed Deep Networks NeurIPS 2012 Large-scale Linear Support Vector Regression JMLR 2012 Latent Graphical Model Selection: Efficient Methods for Locally Tree-like Graphs NeurIPS 2012 Learning as MAP Inference in Discrete Graphical Models NeurIPS 2012 Learning curves for multi-task Gaussian process regression NeurIPS 2012 Learning DNF Expressions from Fourier Spectrum COLT 2012 Learning Fourier Sparse Set Functions AISTATS 2012 Learning from Distributions via Support Measure Machines NeurIPS 2012 Learning from the Wisdom of Crowds by Minimax Entropy NeurIPS 2012 Learning from Weak Teachers AISTATS 2012