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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)

Faster Algorithms for Max-Product Message-Passing JMLR 2011 Finite Time Analysis of Stratified Sampling for Monte Carlo NeurIPS 2011 Finite-Time Regional Verification of Stochastic Nonlinear Systems RSS 2011 Follow-the-Regularized-Leader and Mirror Descent: Equivalence Theorems and L1 Regularization AISTATS 2011 From Bandits to Experts: On the Value of Side-Observations NeurIPS 2011 From Stochastic Nonlinear Integrate-and-Fire to Generalized Linear Models NeurIPS 2011 Gaussian process modulated renewal processes NeurIPS 2011 Gaussian Process Training with Input Noise NeurIPS 2011 Generalised Coupled Tensor Factorisation NeurIPS 2011 Generalization Bound for Infinitely Divisible Empirical Process AISTATS 2011 Generalization Bounds and Consistency for Latent Structural Probit and Ramp Loss NeurIPS 2011 Generalized Beta Mixtures of Gaussians NeurIPS 2011 Generalized Lasso based Approximation of Sparse Coding for Visual Recognition NeurIPS 2011 Generalized TD Learning JMLR 2011 Generative Kernels for Exponential Families AISTATS 2011 Greedy Algorithms for Structurally Constrained High Dimensional Problems NeurIPS 2011 Greedy Model Averaging NeurIPS 2011 Group Lasso Estimation of High-dimensional Covariance Matrices JMLR 2011 Hashing Algorithms for Large-Scale Learning NeurIPS 2011 Heavy-tailed Distances for Gradient Based Image Descriptors NeurIPS 2011 Hierarchical Knowledge Gradient for Sequential Sampling JMLR 2011 Hierarchical Probabilistic Models for Group Anomaly Detection AISTATS 2011 Hierarchical Topic Modeling for Analysis of Time-Evolving Personal Choices NeurIPS 2011 High-Dimensional Graphical Model Selection: Tractable Graph Families and Necessary Conditions NeurIPS 2011 High-dimensional regression with noisy and missing data: Provable guarantees with non-convexity NeurIPS 2011