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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)

Learning Set Functions with Limited Complementarity AAAI 2019 Learning Sparse Distributions using Iterative Hard Thresholding NeurIPS 2019 Learning Stable Deep Dynamics Models NeurIPS 2019 Learning step sizes for unfolded sparse coding NeurIPS 2019 Learning Strictly Orthogonal p-Order Nonnegative Laplacian Embedding via Smoothed Iterative Reweighted Method IJCAI 2019 Learning Swarm Behaviors using Grammatical Evolution and Behavior Trees IJCAI 2019 Learning to bid in revenue-maximizing auctions ICML 2019 Learning to Calibrate Straight Lines for Fisheye Image Rectification CVPR 2019 Learning to Collaborate in Markov Decision Processes ICML 2019 Learning to Correlate in Multi-Player General-Sum Sequential Games NeurIPS 2019 Learning to Explore Intrinsic Saliency for Stereoscopic Video CVPR 2019 Learning to Find Common Objects Across Few Image Collections ICCV 2019 Learning to Learn Gradient Aggregation by Gradient Descent IJCAI 2019 Learning-to-Learn Stochastic Gradient Descent with Biased Regularization ICML 2019 Learning to Match via Inverse Optimal Transport JMLR 2019 Learning to Optimize in Swarms NeurIPS 2019 Learning to Optimize under Non-Stationarity AISTATS 2019 Learning to Perform Local Rewriting for Combinatorial Optimization NeurIPS 2019 Learning to Rank for Plausible Plausibility ACL 2019 Learning to Route in Similarity Graphs ICML 2019 Learning to Sample CVPR 2019 Learning to Sample Hard Instances for Graph Algorithms ACML 2019 Learning to Screen NeurIPS 2019 Learning to select for a predefined ranking ICML 2019 Learning To Simulate ICLR 2019