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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)

Stochastic Flows and Geometric Optimization on the Orthogonal Group ICML 2020 Stochastic Frank-Wolfe for Constrained Finite-Sum Minimization ICML 2020 Stochastic Gauss-Newton Algorithms for Nonconvex Compositional Optimization ICML 2020 Stochastic Gradient and Langevin Processes ICML 2020 Stochastic Gradient Descent in Correlated Settings: A Study on Gaussian Processes NeurIPS 2020 Stochastic Hamiltonian Gradient Methods for Smooth Games ICML 2020 Stochasticity of Deterministic Gradient Descent: Large Learning Rate for Multiscale Objective Function NeurIPS 2020 Stochastic Linear Contextual Bandits with Diverse Contexts AISTATS 2020 Stochastic Loss Function AAAI 2020 Stochastic Nested Variance Reduction for Nonconvex Optimization JMLR 2020 Stochastic Neural Network with Kronecker Flow AISTATS 2020 Stochastic Normalizing Flows NeurIPS 2020 Stochastic Online Learning with Probabilistic Graph Feedback AAAI 2020 Stochastic Optimization for Non-convex Inf-Projection Problems ICML 2020 Stochastic Optimization for Performative Prediction NeurIPS 2020 Stochastic Optimization for Regularized Wasserstein Estimators ICML 2020 Stochastic Optimization with Heavy-Tailed Noise via Accelerated Gradient Clipping NeurIPS 2020 Stochastic Optimization with Laggard Data Pipelines NeurIPS 2020 Stochastic Particle-Optimization Sampling and the Non-Asymptotic Convergence Theory AISTATS 2020 StochasticRank: Global Optimization of Scale-Free Discrete Functions ICML 2020 Stochastic Recursive Gradient Descent Ascent for Stochastic Nonconvex-Strongly-Concave Minimax Problems NeurIPS 2020 Stochastic Regret Minimization in Extensive-Form Games ICML 2020 Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty NeurIPS 2020 Stochastic Sparse Subspace Clustering CVPR 2020 Stochastic Stein Discrepancies NeurIPS 2020