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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)

Disentangling Adversarial Robustness and Generalization CVPR 2019 Dispatching Through Pricing: Modeling Ride-Sharing and Designing Dynamic Prices IJCAI 2019 DistillHash: Unsupervised Deep Hashing by Distilling Data Pairs CVPR 2019 Distributed Collaborative Feature Selection Based on Intermediate Representation IJCAI 2019 Distributed Community Detection via Metastability of the 2-Choices Dynamics AAAI 2019 Distributed estimation of the inverse Hessian by determinantal averaging NeurIPS 2019 Distributed Inexact Newton-type Pursuit for Non-convex Sparse Learning AISTATS 2019 Distributed Inference for Linear Support Vector Machine JMLR 2019 Distributed Learning over Unreliable Networks ICML 2019 Distributed Learning with Sublinear Communication ICML 2019 Distributed Low-rank Matrix Factorization With Exact Consensus NeurIPS 2019 Distributed Maximization of "Submodular plus Diversity" Functions for Multi-label Feature Selection on Huge Datasets AISTATS 2019 Distributed PageRank Computation: An Improved Theoretical Study AAAI 2019 Distributed Representation of Words in Cause and Effect Spaces AAAI 2019 Distributed Weighted Matching via Randomized Composable Coresets ICML 2019 DISTRIBUTIONAL CONCAVITY REGULARIZATION FOR GANS ICLR 2019 Distributionally Adversarial Attack AAAI 2019 Distributionally Robust Language Modeling EMNLP 2019 Distributionally Robust Optimization and Generalization in Kernel Methods NeurIPS 2019 Distributionally Robust Semi-Supervised Learning for People-Centric Sensing AAAI 2019 Distributionally Robust Submodular Maximization AISTATS 2019 Distributional Multivariate Policy Evaluation and Exploration with the Bellman GAN ICML 2019 Distributional reinforcement learning with linear function approximation AISTATS 2019 Distribution calibration for regression ICML 2019 Distribution-Dependent Analysis of Gibbs-ERM Principle COLT 2019