convex optimization

Localization, Convexity, and Star Aggregation NeurIPS 2021 Local Search Algorithms for Rank-Constrained Convex Optimization ICLR 2021 Local SGD: Unified Theory and New Efficient Methods AISTATS 2021 Logistic Q-Learning AISTATS 2021 Lower Bounds and Optimal Algorithms for Smooth and Strongly Convex Decentralized Optimization Over Time-Varying Networks NeurIPS 2021 Low-Rank Extragradient Method for Nonsmooth and Low-Rank Matrix Optimization Problems NeurIPS 2021 Low Resource Quadratic Forms for Knowledge Graph Embeddings EMNLP 2021 Matrix Completion with Model-free Weighting ICML 2021 Mirrorless Mirror Descent: A Natural Derivation of Mirror Descent AISTATS 2021 Model-Targeted Poisoning Attacks with Provable Convergence ICML 2021 (Nearly) Dimension Independent Private ERM with AdaGrad Rates\{via Publicly Estimated Subspaces COLT 2021 Near-Optimal Lower Bounds For Convex Optimization For All Orders of Smoothness NeurIPS 2021 Oblivious Sketching-based Central Path Method for Linear Programming ICML 2021 One-Shot Federated Learning: Theoretical Limits and Algorithms to Achieve Them JMLR 2021 One-sided Frank-Wolfe algorithms for saddle problems ICML 2021 Online A-Optimal Design and Active Linear Regression ICML 2021 On the Convergence of Langevin Monte Carlo: The Interplay between Tail Growth and Smoothness COLT 2021 Optimal Non-Convex Exact Recovery in Stochastic Block Model via Projected Power Method ICML 2021 Optimal regret algorithm for Pseudo-1d Bandit Convex Optimization ICML 2021 Optimized auxiliary particle filters: adapting mixture proposals via convex optimization UAI 2021 Optimized Score Transformation for Consistent Fair Classification JMLR 2021 Optimizing Optimizers: Regret-optimal gradient descent algorithms COLT 2021 Outlier-Robust Optimal Transport ICML 2021 Outside the Echo Chamber: Optimizing the Performative Risk ICML 2021 Overcoming the Convex Barrier for Simplex Inputs NeurIPS 2021