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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)

Learning Multiple Models via Regularized Weighting NeurIPS 2013 Learning Near-Optimal Cost-Sensitive Decision Policy for Object Detection ICCV 2013 Learning Optimally Sparse Support Vector Machines ICML 2013 Learning Policies for Contextual Submodular Prediction ICML 2013 Learning Prices for Repeated Auctions with Strategic Buyers NeurIPS 2013 Learning Social Infectivity in Sparse Low-rank Networks Using Multi-dimensional Hawkes Processes AISTATS 2013 Learning Spatio-Temporal Structure from RGB-D Videos for Human Activity Detection and Anticipation ICML 2013 Learning Stochastic Inverses NeurIPS 2013 Learning Structured Low-Rank Representations for Image Classification CVPR 2013 Learning the beta-Divergence in Tweedie Compound Poisson Matrix Factorization Models ICML 2013 Learning Theory Analysis for Association Rules and Sequential Event Prediction JMLR 2013 Learning to Detect Partially Overlapping Instances CVPR 2013 Learning to Estimate and Remove Non-uniform Image Blur CVPR 2013 Learning to Pass Expectation Propagation Messages NeurIPS 2013 Learning Trees from Strings: A Strong Learning Algorithm for some Context-Free Grammars JMLR 2013 Learning Triggering Kernels for Multi-dimensional Hawkes Processes ICML 2013 Learning Using Local Membership Queries COLT 2013 Learning with Invariance via Linear Functionals on Reproducing Kernel Hilbert Space NeurIPS 2013 Learning with Noisy Labels NeurIPS 2013 Least Informative Dimensions NeurIPS 2013 Least Soft-Threshold Squares Tracking CVPR 2013 Lexical and Hierarchical Topic Regression NeurIPS 2013 Linear Approximation to ADMM for MAP inference ACML 2013 Linear Convergence with Condition Number Independent Access of Full Gradients NeurIPS 2013 Linear decision rule as aspiration for simple decision heuristics NeurIPS 2013