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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)

Controlling Posterior Collapse by an Inverse Lipschitz Constraint on the Decoder Network ICML 2023 Controlling Wasserstein Distances by Kernel Norms with Application to Compressive Statistical Learning JMLR 2023 Convergence Analysis of Sequential Federated Learning on Heterogeneous Data NeurIPS 2023 Convergence and Diversity in the Control Hierarchy ACL 2023 Convergence of Actor-Critic with Multi-Layer Neural Networks NeurIPS 2023 Convergence of AdaGrad for Non-convex Objectives: Simple Proofs and Relaxed Assumptions COLT 2023 Convergence of Adam Under Relaxed Assumptions NeurIPS 2023 Convergence of Alternating Gradient Descent for Matrix Factorization NeurIPS 2023 Convergence of First-Order Methods for Constrained Nonconvex Optimization with Dependent Data ICML 2023 Convergence of mean-field Langevin dynamics: time-space discretization, stochastic gradient, and variance reduction NeurIPS 2023 Convergence of Proximal Point and Extragradient-Based Methods Beyond Monotonicity: the Case of Negative Comonotonicity ICML 2023 Convergence of score-based generative modeling for general data distributions ALT 2023 Convergence of Stein Variational Gradient Descent under a Weaker Smoothness Condition AISTATS 2023 Convergence Rates of a Class of Multivariate Density Estimation Methods Based on Adaptive Partitioning JMLR 2023 Convex and Non-convex Optimization Under Generalized Smoothness NeurIPS 2023 Convex Reinforcement Learning in Finite Trials JMLR 2023 Convolutional Neural Operators for robust and accurate learning of PDEs NeurIPS 2023 Convolutional Persistence as a Remedy to Neural Model Analysis AISTATS 2023 Convolutional State Space Models for Long-Range Spatiotemporal Modeling NeurIPS 2023 Convolution Monge Mapping Normalization for learning on sleep data NeurIPS 2023 COOP: Decoupling and Coupling of Whole-Body Grasping Pose Generation ICCV 2023 Cooperation or Competition: Avoiding Player Domination for Multi-Target Robustness via Adaptive Budgets CVPR 2023 Coop: Memory is not a Commodity NeurIPS 2023 Coordinated Dynamic Bidding in Repeated Second-Price Auctions with Budgets ICML 2023 Coordinate Descent Methods for DC Minimization: Optimality Conditions and Global Convergence AAAI 2023