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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

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52
352
828
3,646
5,854
2000
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Papers (including subtopics)

Universal consistency and minimax rates for online Mondrian Forests NeurIPS 2017 Universality of Bayesian mixture predictors ALT 2017 Unrolling the Shutter: CNN to Correct Motion Distortions CVPR 2017 Unsatisfiable Core Shrinking for Anytime Answer Set Optimization IJCAI 2017 Unsupervised Dialogue Act Induction using Gaussian Mixtures EACL 2017 Unsupervised Sequential Sensor Acquisition AISTATS 2017 Unsupervised Text Segmentation Based on Native Language Characteristics ACL 2017 Unsupervised Training for Large Vocabulary Translation Using Sparse Lexicon and Word Classes EACL 2017 VAE Learning via Stein Variational Gradient Descent NeurIPS 2017 Value-Aware Loss Function for Model-based Reinforcement Learning AISTATS 2017 Variable Importance Using Decision Trees NeurIPS 2017 Variance-based Regularization with Convex Objectives NeurIPS 2017 Variants of RMSProp and Adagrad with Logarithmic Regret Bounds ICML 2017 Variational Bayesian Multiple Instance Learning With Gaussian Processes CVPR 2017 Variational Boosting: Iteratively Refining Posterior Approximations ICML 2017 Variational Dropout Sparsifies Deep Neural Networks ICML 2017 Variational Inference for Gaussian Process Models with Linear Complexity NeurIPS 2017 Variational Inference for Sparse and Undirected Models ICML 2017 Variational Inference via χ Upper Bound Minimization NeurIPS 2017 Variational Mixtures of Gaussian Processes for Classification IJCAI 2017 Variational Particle Approximations JMLR 2017 Variational Policy for Guiding Point Processes ICML 2017 Variational Recurrent Neural Networks for Speech Separation Interspeech 2017 Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net NeurIPS 2017 Verifying Fault-tolerance in Parameterised Multi-Agent Systems IJCAI 2017