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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)

Combining Pessimism with Optimism for Robust and Efficient Model-Based Deep Reinforcement Learning ICML 2021 Combining Physics and Machine Learning for Network Flow Estimation ICLR 2021 Combining pseudo-point and state space approximations for sum-separable Gaussian Processes UAI 2021 Combining Reinforcement Learning and Constraint Programming for Combinatorial Optimization AAAI 2021 Combining Reinforcement Learning with Lin-Kernighan-Helsgaun Algorithm for the Traveling Salesman Problem AAAI 2021 COMBO: Conservative Offline Model-Based Policy Optimization NeurIPS 2021 CombOptNet: Fit the Right NP-Hard Problem by Learning Integer Programming Constraints ICML 2021 Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity ICLR 2021 Communication-Aware Collaborative Learning AAAI 2021 Communication-Efficient Agnostic Federated Averaging Interspeech 2021 Communication-Efficient Distributed Covariance Sketch, with Application to Distributed PCA JMLR 2021 Communication-Efficient Frank-Wolfe Algorithm for Nonconvex Decentralized Distributed Learning AAAI 2021 Communication efficient parallel reinforcement learning UAI 2021 Communication Efficient Primal-Dual Algorithm for Nonconvex Nonsmooth Distributed Optimization AISTATS 2021 Communication-efficient SGD: From Local SGD to One-Shot Averaging NeurIPS 2021 Communication Efficient SGD via Gradient Sampling With Bayes Prior CVPR 2021 Comparing Test Sets with Item Response Theory ACL 2021 Comparing Text Representations: A Theory-Driven Approach EMNLP 2021 Comparing the Value of Labeled and Unlabeled Data in Method-of-Moments Latent Variable Estimation AISTATS 2021 Comparison Lift: Bandit-based Experimentation System for Online Advertising AAAI 2021 Compatibility-Aware Heterogeneous Visual Search CVPR 2021 Competing AI: How does competition feedback affect machine learning? AISTATS 2021 Completing the Picture: Randomized Smoothing Suffers from the Curse of Dimensionality for a Large Family of Distributions AISTATS 2021 Complexity Lower Bounds for Nonconvex-Strongly-Concave Min-Max Optimization NeurIPS 2021 Composite Adversarial Attacks AAAI 2021