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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)

Training Deep Neural Networks via Direct Loss Minimization ICML 2016 Training Region-Based Object Detectors With Online Hard Example Mining CVPR 2016 Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation NeurIPS 2016 Truthful Univariate Estimators ICML 2016 Twin Model G-PLDA for Duration Mismatch Compensation in Text-Independent Speaker Verification Interspeech 2016 Two-Stage Temporal Processing for Single-Channel Speech Enhancement Interspeech 2016 Unbounded Bayesian Optimization via Regularization AISTATS 2016 Uncertainty-Driven 6D Pose Estimation of Objects and Scenes From a Single RGB Image CVPR 2016 Unconstrained Salient Object Detection via Proposal Subset Optimization CVPR 2016 Unifying Count-Based Exploration and Intrinsic Motivation NeurIPS 2016 Unitary Evolution Recurrent Neural Networks ICML 2016 Universal Approximation Results for the Temporal Restricted Boltzmann Machine and the Recurrent Temporal Restricted Boltzmann Machine JMLR 2016 Universal Models of Multivariate Temporal Point Processes AISTATS 2016 Unsupervised Learning from Noisy Networks with Applications to Hi-C Data NeurIPS 2016 Unsupervised Risk Estimation Using Only Conditional Independence Structure NeurIPS 2016 Unsupervised Stress Information Labeling Using Gaussian Process Latent Variable Model for Statistical Speech Synthesis Interspeech 2016 Using Kernel Methods and Model Selection for Prediction of Preterm Birth MLHC 2016 Using Social Dynamics to Make Individual Predictions: Variational Inference with a Stochastic Kinetic Model NeurIPS 2016 Variance-Reduced and Projection-Free Stochastic Optimization ICML 2016 Variance Reduction for Faster Non-Convex Optimization ICML 2016 Variance Reduction in Stochastic Gradient Langevin Dynamics NeurIPS 2016 Variational Bayes on Monte Carlo Steroids NeurIPS 2016 Variational Gaussian Copula Inference AISTATS 2016 Variational Inference for Monte Carlo Objectives ICML 2016 Variational Inference in Mixed Probabilistic Submodular Models NeurIPS 2016