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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)

Robust and Heavy-Tailed Mean Estimation Made Simple, via Regret Minimization NeurIPS 2020 Robust Asynchronous Stochastic Gradient-Push: Asymptotically Optimal and Network-Independent Performance for Strongly Convex Functions JMLR 2020 Robust Bayesian Classification Using An Optimistic Score Ratio ICML 2020 Robust Beam Search for Encoder-Decoder Attention Based Speech Recognition Without Length Bias Interspeech 2020 Robust causal inference under covariate shift via worst-case subpopulation treatment effects COLT 2020 Robust compressed sensing using generative models NeurIPS 2020 Robust Deep Learning as Optimal Control: Insights and Convergence Guarantees L4DC 2020 Robust Deep Ordinal Regression under Label Noise ACML 2020 Robust Density Estimation under Besov IPM Losses NeurIPS 2020 Robust Design of Deep Neural Networks Against Adversarial Attacks Based on Lyapunov Theory CVPR 2020 Robust Document Distance with Wasserstein-Fisher-Rao metric ACML 2020 Robust estimation of local affine maps and its applications to image matching WACV 2020 Robust Federated Learning: The Case of Affine Distribution Shifts NeurIPS 2020 Robust Gaussian Covariance Estimation in Nearly-Matrix Multiplication Time NeurIPS 2020 Robust Gradient-Based Markov Subsampling AAAI 2020 Robust guarantees for learning an autoregressive filter ALT 2020 Robust high dimensional learning for Lipschitz and convex losses JMLR 2020 Robust Homography Estimation via Dual Principal Component Pursuit CVPR 2020 Robust large-margin learning in hyperbolic space NeurIPS 2020 Robust Learning from Discriminative Feature Feedback AISTATS 2020 Robust Learning with the Hilbert-Schmidt Independence Criterion ICML 2020 Robust Machine Reading Comprehension by Learning Soft labels COLING 2020 Robust modal regression with direct gradient approximation of modal regression risk UAI 2020 Robust Multi-Object Matching via Iterative Reweighting of the Graph Connection Laplacian NeurIPS 2020 Robust Multiple-Path Orienteering Problem: Securing Against Adversarial Attacks RSS 2020