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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)

Variational Information Maximization for Feature Selection NeurIPS 2016 Variational Tempering AISTATS 2016 Verification Based Solution for Structured MAB Problems NeurIPS 2016 VIME: Variational Information Maximizing Exploration NeurIPS 2016 Virtual Machines and Containers as a Platform for Experimentation Interspeech 2016 Visual Dynamics: Probabilistic Future Frame Synthesis via Cross Convolutional Networks NeurIPS 2016 Voice Conversion Based on Matrix Variate Gaussian Mixture Model Using Multiple Frame Features Interspeech 2016 Volumetric Spanners: An Efficient Exploration Basis for Learning JMLR 2016 Wasserstein Training of Restricted Boltzmann Machines NeurIPS 2016 Weak Convergence Properties of Constrained Emphatic Temporal-difference Learning with Constant and Slowly Diminishing Stepsize JMLR 2016 Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks NeurIPS 2016 What Makes Word-level Neural Machine Translation Hard: A Case Study on English-German Translation COLING 2016 When can we rank well from comparisons of O(n\log(n)) non-actively chosen pairs? COLT 2016 Why Most Decisions Are Easy in Tetris—And Perhaps in Other Sequential Decision Problems, As Well ICML 2016 Why Regularized Auto-Encoders learn Sparse Representation? ICML 2016 Without-Replacement Sampling for Stochastic Gradient Methods NeurIPS 2016 XFT: Practical Fault Tolerance beyond Crashes OSDI 2016 Yggdrasil: An Optimized System for Training Deep Decision Trees at Scale NeurIPS 2016 3D Shape Estimation From 2D Landmarks: A Convex Relaxation Approach CVPR 2015 A Bayes consistent 1-NN classifier AISTATS 2015 A Bayesian nonparametric procedure for comparing algorithms ICML 2015 Abstraction Selection in Model-based Reinforcement Learning ICML 2015 Accelerated Mirror Descent in Continuous and Discrete Time NeurIPS 2015 Accelerated Proximal Gradient Methods for Nonconvex Programming NeurIPS 2015 Accurate and conservative estimates of MRF log-likelihood using reverse annealing AISTATS 2015