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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)

Uniqueness of Tensor Decompositions with Applications to Polynomial Identifiability COLT 2014 Universal Matrix Completion ICML 2014 Using Trajectory Data to Improve Bayesian Optimization for Reinforcement Learning JMLR 2014 Variational Gaussian Inference for Bilinear Models of Count Data ACML 2014 Variational Gaussian Process State-Space Models NeurIPS 2014 Variational Inference for Sequential Distance Dependent Chinese Restaurant Process ICML 2014 Visual Tracking via Probability Continuous Outlier Model CVPR 2014 Volumetric Spanners: an Efficient Exploration Basis for Learning COLT 2014 Von Mises-Fisher Clustering Models ICML 2014 Wasserstein Propagation for Semi-Supervised Learning ICML 2014 What Regularized Auto-Encoders Learn from the Data-Generating Distribution JMLR 2014 Zeta Hull Pursuits: Learning Nonconvex Data Hulls NeurIPS 2014 3D Sub-query Expansion for Improving Sketch-Based Multi-view Image Retrieval ICCV 2013 A Bayesian Approach to Multimodal Visual Dictionary Learning CVPR 2013 ABC Reinforcement Learning ICML 2013 Accelerated Coordinate Descent with Adaptive Coordinate Frequencies ACML 2013 Accelerated Mini-Batch Stochastic Dual Coordinate Ascent NeurIPS 2013 Accelerating Stochastic Gradient Descent using Predictive Variance Reduction NeurIPS 2013 Accurate and Robust Registration of Nonrigid Surface Using Hierarchical Statistical Shape Model CVPR 2013 Achievability of Asymptotic Minimax Regret in Online and Batch Prediction ACML 2013 A Comparative Framework for Preconditioned Lasso Algorithms NeurIPS 2013 A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problems CVPR 2013 A Competitive Test for Uniformity of Monotone Distributions AISTATS 2013 A Convex Optimization Framework for Active Learning ICCV 2013 A C++ Template-Based Reinforcement Learning Library: Fitting the Code to the Mathematics JMLR 2013