convex optimization

Relative Interior Rule in Block-Coordinate Descent CVPR 2020 Robust Market Equilibria with Uncertain Preferences AAAI 2020 Robust Policy Synthesis for Uncertain POMDPs via Convex Optimization IJCAI 2020 SAdam: A Variant of Adam for Strongly Convex Functions ICLR 2020 Sampling Without Compromising Accuracy in Adaptive Data Analysis ALT 2020 Scalable Calibration of Affinity Matrices from Incomplete Observations ACML 2020 Sharp Asymptotics and Optimal Performance for Inference in Binary Models AISTATS 2020 Spectral Frank-Wolfe Algorithm: Strict Complementarity and Linear Convergence ICML 2020 Stochastic Conditional Gradient Methods: From Convex Minimization to Submodular Maximization JMLR 2020 Stochastic Coordinate Minimization with Progressive Precision for Stochastic Convex Optimization ICML 2020 Stochastic Optimization with Heavy-Tailed Noise via Accelerated Gradient Clipping NeurIPS 2020 Stochastic Optimization with Laggard Data Pipelines NeurIPS 2020 Stochastic Subspace Cubic Newton Method ICML 2020 Tchebycheff Procedure for Multi-task Text Classification ACL 2020 Theory of Curriculum Learning, with Convex Loss Functions JMLR 2020 The Strong Screening Rule for SLOPE NeurIPS 2020 The Wasserstein Proximal Gradient Algorithm NeurIPS 2020 Thunder: a Fast Coordinate Selection Solver for Sparse Learning NeurIPS 2020 Transparency Promotion with Model-Agnostic Linear Competitors ICML 2020 Understanding spiking networks through convex optimization NeurIPS 2020 Variance Reduction via Accelerated Dual Averaging for Finite-Sum Optimization NeurIPS 2020 Accelerating Rescaled Gradient Descent: Fast Optimization of Smooth Functions NeurIPS 2019 Adaptation Based on Generalized Discrepancy JMLR 2019 A Dynamical Systems Perspective on Nesterov Acceleration ICML 2019 A Generic Acceleration Framework for Stochastic Composite Optimization NeurIPS 2019