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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)

Robust and Scalable Bayesian Online Changepoint Detection ICML 2023 Robust Average-Reward Markov Decision Processes AAAI 2023 Robust Bayesian Satisficing NeurIPS 2023 Robust Budget Pacing with a Single Sample ICML 2023 Robust Camera Pose Refinement for Multi-Resolution Hash Encoding ICML 2023 Robust Causal Graph Representation Learning against Confounding Effects AAAI 2023 Robust Collaborative Learning with Linear Gradient Overhead ICML 2023 Robust Concept Erasure via Kernelized Rate-Distortion Maximization NeurIPS 2023 Robust Consensus in Ranking Data Analysis: Definitions, Properties and Computational Issues ICML 2023 Robust Data Valuation with Weighted Banzhaf Values NeurIPS 2023 Robust distillation for worst-class performance: on the interplay between teacher and student objectives UAI 2023 Robust Distributed Learning: Tight Error Bounds and Breakdown Point under Data Heterogeneity NeurIPS 2023 Robust Empirical Risk Minimization with Tolerance ALT 2023 Robust e-NeRF: NeRF from Sparse & Noisy Events under Non-Uniform Motion ICCV 2023 Robust Estimation of Discrete Distributions under Local Differential Privacy ALT 2023 Robust Gaussian process regression with the trimmed marginal likelihood UAI 2023 Robust Generalization Against Photon-Limited Corruptions via Worst-Case Sharpness Minimization CVPR 2023 Robust Heterogeneous Federated Learning under Data Corruption ICCV 2023 Robust High-Dimensional Low-Rank Matrix Estimation: Optimal Rate and Data-Adaptive Tuning JMLR 2023 Robust Image Classification via Using Multiple Diversity Losses ACML 2023 Robust Learning with Progressive Data Expansion Against Spurious Correlation NeurIPS 2023 Robust Linear Regression for General Feature Distribution AISTATS 2023 Robust Linear Regression: Gradient-descent, Early-stopping, and Beyond AISTATS 2023 Robust Lipschitz Bandits to Adversarial Corruptions NeurIPS 2023 Robust low-rank training via approximate orthonormal constraints NeurIPS 2023