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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

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52
352
828
3,646
5,854
2000
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Papers (including subtopics)

A Domain-Shrinking based Bayesian Optimization Algorithm with Order-Optimal Regret Performance NeurIPS 2021 A Dual Iterative Refinement Method for Non-Rigid Shape Matching CVPR 2021 AdvantageNAS: Efficient Neural Architecture Search with Credit Assignment AAAI 2021 Adversarial Attack Generation Empowered by Min-Max Optimization NeurIPS 2021 Adversarial Dueling Bandits ICML 2021 Adversarial Examples for k-Nearest Neighbor Classifiers Based on Higher-Order Voronoi Diagrams NeurIPS 2021 Adversarial Examples in Multi-Layer Random ReLU Networks NeurIPS 2021 Adversarial Imaging Pipelines CVPR 2021 Adversarially Robust Estimate and Risk Analysis in Linear Regression AISTATS 2021 Adversarially robust learning for security-constrained optimal power flow NeurIPS 2021 Adversarially Robust Learning with Unknown Perturbation Sets COLT 2021 Adversarial Mixing Policy for Relaxing Locally Linear Constraints in Mixup EMNLP 2021 Adversarial Online Learning with Changing Action Sets: Efficient Algorithms with Approximate Regret Bounds ALT 2021 Adversarial Regression with Doubly Non-negative Weighting Matrices NeurIPS 2021 Adversarial Regularization as Stackelberg Game: An Unrolled Optimization Approach EMNLP 2021 Adversarial Robustness Guarantees for Random Deep Neural Networks ICML 2021 Adversarial Robustness of Streaming Algorithms through Importance Sampling NeurIPS 2021 Adversarial Robustness Under Long-Tailed Distribution CVPR 2021 Adversarial score matching and improved sampling for image generation ICLR 2021 Adversarial Spectral Kernel Matching for Unsupervised Time Series Domain Adaptation IJCAI 2021 Adversarial Training and Provable Robustness: A Tale of Two Objectives AAAI 2021 Advice-Guided Reinforcement Learning in a non-Markovian Environment AAAI 2021 A Dynamical View on Optimization Algorithms of Overparameterized Neural Networks AISTATS 2021 A Fast and Robust Method for Global Topological Functional Optimization AISTATS 2021 A Faster Decentralized Algorithm for Nonconvex Minimax Problems NeurIPS 2021