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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)

Regularized Weighted Low Rank Approximation NeurIPS 2019 Regularizing Model-Based Planning with Energy-Based Models CoRL 2019 Regularizing Neural Networks via Stochastic Branch Layers ACML 2019 Reinforcement Learning based Curriculum Optimization for Neural Machine Translation NAACL 2019 Reinforcement Learning with Convex Constraints NeurIPS 2019 Relating RNN Layers with the Spectral WFA Ranks in Sequence Modelling ACL 2019 Relative Error Bound Analysis for Nuclear Norm Regularized Matrix Completion JMLR 2019 Relaxed Parameter Sharing: Effectively Modeling Time-Varying Relationships in Clinical Time-Series MLHC 2019 Relaxing and Restraining Queries for OBDA AAAI 2019 Reliable training and estimation of variance networks NeurIPS 2019 RENAS: Reinforced Evolutionary Neural Architecture Search CVPR 2019 Renyi Differentially Private ERM for Smooth Objectives AISTATS 2019 REPAIR: Removing Representation Bias by Dataset Resampling CVPR 2019 Reparameterizable Subset Sampling via Continuous Relaxations IJCAI 2019 Reparameterizing Distributions on Lie Groups AISTATS 2019 RePr: Improved Training of Convolutional Filters CVPR 2019 ResNet and Batch-normalization Improve Data Separability ACML 2019 Resource Constrained Neural Network Architecture Search: Will a Submodularity Assumption Help? ICCV 2019 RES-PCA: A Scalable Approach to Recovering Low-Rank Matrices CVPR 2019 Restoration of Non-Rigidly Distorted Underwater Images Using a Combination of Compressive Sensing and Local Polynomial Image Representations ICCV 2019 Rethinking Generative Mode Coverage: A Pointwise Guaranteed Approach NeurIPS 2019 Rethinking Loss Design for Large-scale 3D Shape Retrieval IJCAI 2019 Rethinking Lossy Compression: The Rate-Distortion-Perception Tradeoff ICML 2019 Rethinking the CSC Model for Natural Images NeurIPS 2019 Rethinking the Discount Factor in Reinforcement Learning: A Decision Theoretic Approach AAAI 2019