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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)

The asymptotic spectrum of the Hessian of DNN throughout training ICLR 2020 The Boomerang Sampler ICML 2020 The Break-Even Point on Optimization Trajectories of Deep Neural Networks ICLR 2020 The Choice Function Framework for Online Policy Improvement AAAI 2020 The Competitive Effects of Variance-based Pricing IJCAI 2020 The Complexity of Adversarially Robust Proper Learning of Halfspaces with Agnostic Noise NeurIPS 2020 The Complexity of Computing Maximin Share Allocations on Graphs AAAI 2020 The Complexity of Finding Stationary Points with Stochastic Gradient Descent ICML 2020 The Computational Complexity of Angry Birds (Extended Abstract) IJCAI 2020 The Convex Relaxation Barrier, Revisited: Tightened Single-Neuron Relaxations for Neural Network Verification NeurIPS 2020 The Cost-free Nature of Optimally Tuning Tikhonov Regularizers and Other Ordered Smoothers ICML 2020 The Curse of Performance Instability in Analysis Datasets: Consequences, Source, and Suggestions EMNLP 2020 The Devil is in the Detail: A Framework for Macroscopic Prediction via Microscopic Models NeurIPS 2020 The Devil Is in the Details: Delving Into Unbiased Data Processing for Human Pose Estimation CVPR 2020 The Differentiable Cross-Entropy Method ICML 2020 The Discrete Gaussian for Differential Privacy NeurIPS 2020 The Early Phase of Neural Network Training ICLR 2020 The EM Algorithm gives Sample-Optimality for Learning Mixtures of Well-Separated Gaussians COLT 2020 The EOS Decision and Length Extrapolation EMNLP 2020 The Error-Feedback framework: SGD with Delayed Gradients JMLR 2020 The estimation error of general first order methods COLT 2020 The Expressive Power of a Class of Normalizing Flow Models AISTATS 2020 The Gambler's Problem and Beyond ICLR 2020 The Generalization-Stability Tradeoff In Neural Network Pruning NeurIPS 2020 The Generalized Lasso with Nonlinear Observations and Generative Priors NeurIPS 2020