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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)

Asymptotic Analysis via Stochastic Differential Equations of Gradient Descent Algorithms in Statistical and Computational Paradigms JMLR 2020 Asymptotic Consistency of α-Rényi-Approximate Posteriors JMLR 2020 Asymptotic Errors for High-Dimensional Convex Penalized Linear Regression beyond Gaussian Matrices COLT 2020 Asymptotic Guarantees for Generative Modeling Based on the Smooth Wasserstein Distance NeurIPS 2020 Asymptotic normality and confidence intervals for derivatives of 2-layers neural network in the random features model NeurIPS 2020 Asymptotic Risk of Bézier Simplex Fitting AAAI 2020 Asymptotics of Wide Networks from Feynman Diagrams ICLR 2020 Asynchronous Coagent Networks ICML 2020 Asynchronous Gibbs Sampling AISTATS 2020 AsyncQVI: Asynchronous-Parallel Q-Value Iteration for Discounted Markov Decision Processes with Near-Optimal Sample Complexity AISTATS 2020 A Tale of Two-Timescale Reinforcement Learning with the Tightest Finite-Time Bound AAAI 2020 A Tensor Compiler for Unified Machine Learning Prediction Serving OSDI 2020 A Theoretical and Practical Framework for Regression and Classification from Truncated Samples AISTATS 2020 A Theoretical Case Study of Structured Variational Inference for Community Detection AISTATS 2020 A Theoretical Framework for Target Propagation NeurIPS 2020 A Theory of Usable Information under Computational Constraints ICLR 2020 A Three Sample Hypothesis Test for Evaluating Generative Models AISTATS 2020 A Tight and Unified Analysis of Gradient-Based Methods for a Whole Spectrum of Differentiable Games AISTATS 2020 A Tight Convergence Analysis for Stochastic Gradient Descent with Delayed Updates ALT 2020 AtLoc: Attention Guided Camera Localization AAAI 2020 A Topology Layer for Machine Learning AISTATS 2020 At Stability's Edge: How to Adjust Hyperparameters to Preserve Minima Selection in Asynchronous Training of Neural Networks? ICLR 2020 Attribute Noise Robust Binary Classification (Student Abstract) AAAI 2020 Attribution in Scale and Space CVPR 2020 A Two-level Reinforcement Learning Algorithm for Ambiguous Mean-variance Portfolio Selection Problem IJCAI 2020