smooth optimization

Accelerated Parameter-Free Stochastic Optimization COLT 2024 Quantitative Convergences of Lie Group Momentum Optimizers NeurIPS 2024 Smooth Tchebycheff Scalarization for Multi-Objective Optimization ICML 2024 Explicit Convergence Rates of Greedy and Random Quasi-Newton Methods JMLR 2022 Adaptive Extra-Gradient Methods for Min-Max Optimization and Games ICLR 2021 Optimal and Practical Algorithms for Smooth and Strongly Convex Decentralized Optimization NeurIPS 2020 Blended Conditonal Gradients ICML 2019 A Richer Theory of Convex Constrained Optimization with Reduced Projections and Improved Rates ICML 2017 Limitations on Variance-Reduction and Acceleration Schemes for Finite Sums Optimization NeurIPS 2017 Optimal Black-Box Reductions Between Optimization Objectives NeurIPS 2016 Smooth Imitation Learning for Online Sequence Prediction ICML 2016 Convergence Rates of Inexact Proximal-Gradient Methods for Convex Optimization NeurIPS 2011 Analysis of SVM with Indefinite Kernels NeurIPS 2009 Sparse Metric Learning via Smooth Optimization NeurIPS 2009