Skip to content
conftrace_

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
'5
'10
'15
'20
'25

Papers (including subtopics)

Convergence Rates of Inexact Proximal-Gradient Methods for Convex Optimization NeurIPS 2011 Convergent Decomposition Solvers for Tree-reweighted Free Energies AISTATS 2011 Convergent Fitted Value Iteration with Linear Function Approximation NeurIPS 2011 Convex and Network Flow Optimization for Structured Sparsity JMLR 2011 Convex envelopes of complexity controlling penalties: the case against premature envelopment AISTATS 2011 Crowdclustering NeurIPS 2011 Demixed Principal Component Analysis NeurIPS 2011 Dependent Hierarchical Beta Process for Image Interpolation and Denoising AISTATS 2011 Differentially Private Empirical Risk Minimization JMLR 2011 Differentially Private M-Estimators NeurIPS 2011 Dimensionality Reduction Using the Sparse Linear Model NeurIPS 2011 Directional Statistics on Permutations AISTATS 2011 DirectLiNGAM: A Direct Method for Learning a Linear Non-Gaussian Structural Equation Model JMLR 2011 Dirichlet Process Mixtures of Generalized Linear Models JMLR 2011 Discriminative Learning of Bayesian Networks via Factorized Conditional Log-Likelihood JMLR 2011 Discussion of “A conditional game for comparing approximations” AISTATS 2011 Discussion of “Contextual Bandit Algorithms with Supervised Learning Guarantees” AISTATS 2011 Discussion of “Learning Equivalence Classes of Acyclic Models with Latent and Selection Variables from Multiple Datasets with Overlapping Variables” AISTATS 2011 Discussion of “Spectral Dimensionality Reduction via Maximum Entropy” AISTATS 2011 Discussion of “The Discrete Infinite Logistic Normal Distribution for Mixed-Membership Modeling” AISTATS 2011 Distance Dependent Chinese Restaurant Processes JMLR 2011 Distributed Delayed Stochastic Optimization NeurIPS 2011 Distribution-Independent Evolvability of Linear Threshold Functions COLT 2011 Divide-and-Conquer Matrix Factorization NeurIPS 2011 Does an Efficient Calibrated Forecasting Strategy Exist? COLT 2011