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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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'25

Papers (including subtopics)

Robust Statistical Face Frontalization ICCV 2015 Robust Trajectory Optimization: A Cooperative Stochastic Game Theoretic Approach RSS 2015 Robust Trajectory Optimization Under Frictional Contact with Iterative Learning RSS 2015 Rolling Shutter Super-Resolution ICCV 2015 Safe Exploration for Optimization with Gaussian Processes ICML 2015 Safe Screening for Multi-Task Feature Learning with Multiple Data Matrices ICML 2015 Safe Subspace Screening for Nuclear Norm Regularized Least Squares Problems ICML 2015 SAMOA: Scalable Advanced Massive Online Analysis JMLR 2015 Sample Complexity Bounds for Iterative Stochastic Policy Optimization NeurIPS 2015 Sample Complexity of Episodic Fixed-Horizon Reinforcement Learning NeurIPS 2015 Sample Complexity of Learning Mahalanobis Distance Metrics NeurIPS 2015 Sampling from Probabilistic Submodular Models NeurIPS 2015 Scalable Adaptation of State Complexity for Nonparametric Hidden Markov Models NeurIPS 2015 Scalable Bayesian Optimization Using Deep Neural Networks ICML 2015 Scalable Deep Poisson Factor Analysis for Topic Modeling ICML 2015 Scalable Inference for Gaussian Process Models with Black-Box Likelihoods NeurIPS 2015 Scalable Nonparametric Multiway Data Analysis AISTATS 2015 Scalable Variational Gaussian Process Classification AISTATS 2015 Scalable Variational Inference in Log-supermodular Models ICML 2015 Scale Up Nonlinear Component Analysis with Doubly Stochastic Gradients NeurIPS 2015 Scaling up Natural Gradient by Sparsely Factorizing the Inverse Fisher Matrix ICML 2015 Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks NeurIPS 2015 Second-Order Non-Stationary Online Learning for Regression JMLR 2015 Second-order Quantile Methods for Experts and Combinatorial Games COLT 2015 Secrets of GrabCut and Kernel K-Means ICCV 2015