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Mathematics & Optimization

16,944 papers (0 classified directly here)

Subtopics

Optimization (12,959) Mathematics (5,735) Probability (519) Statistics (265) Discrete Mathematics (15)

Papers per year

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Papers (including subtopics)

Chaining Meets Chain Rule: Multilevel Entropic Regularization and Training of Neural Networks JMLR 2020
Nesterov's Acceleration for Approximate Newton JMLR 2020
A Data Efficient and Feasible Level Set Method for Stochastic Convex Optimization with Expectation Constraints JMLR 2020
Empirical Priors for Prediction in Sparse High-dimensional Linear Regression JMLR 2020
Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral Algorithms JMLR 2020
Distributionally Ambiguous Optimization for Batch Bayesian Optimization JMLR 2020
The Kalai-Smorodinsky solution for many-objective Bayesian optimization JMLR 2020
Dual Iterative Hard Thresholding JMLR 2020
Spectral Algorithms for Community Detection in Directed Networks JMLR 2020
Estimate Sequences for Stochastic Composite Optimization: Variance Reduction, Acceleration, and Robustness to Noise JMLR 2020
Generative Adversarial Nets for Robust Scatter Estimation: A Proper Scoring Rule Perspective JMLR 2020
apricot: Submodular selection for data summarization in Python JMLR 2020
Complete Dictionary Learning via L4-Norm Maximization over the Orthogonal Group JMLR 2020
Breaking the Curse of Nonregularity with Subagging --- Inference of the Mean Outcome under Optimal Treatment Regimes JMLR 2020
Communication-Efficient Distributed Optimization in Networks with Gradient Tracking and Variance Reduction JMLR 2020
Scikit-network: Graph Analysis in Python JMLR 2020
Kriging Prediction with Isotropic Matern Correlations: Robustness and Experimental Designs JMLR 2020
Conic Optimization for Quadratic Regression Under Sparse Noise JMLR 2020
A determinantal point process for column subset selection JMLR 2020
Asymptotic Analysis via Stochastic Differential Equations of Gradient Descent Algorithms in Statistical and Computational Paradigms JMLR 2020
Two-Stage Approach to Multivariate Linear Regression with Sparsely Mismatched Data JMLR 2020
Sobolev Norm Learning Rates for Regularized Least-Squares Algorithms JMLR 2020
On Convergence of Distributed Approximate Newton Methods: Globalization, Sharper Bounds and Beyond JMLR 2020
Provable Convex Co-clustering of Tensors JMLR 2020
Mining Topological Structure in Graphs through Forest Representations JMLR 2020