From post

Faster Rates for the Frank-Wolfe Method over Strongly-Convex Sets.

, и . ICML, том 37 из JMLR Workshop and Conference Proceedings, стр. 541-549. JMLR.org, (2015)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed.

 

Другие публикации лиц с тем же именем

On the Convergence of Projected-Gradient Methods with Low-Rank Projections for Smooth Convex Minimization over Trace-Norm Balls and Related Problems.. SIAM J. Optim., 31 (1): 727-753 (2021)From Oja's Algorithm to the Multiplicative Weights Update Method with Applications.. CoRR, (2023)Linear convergence of Frank-Wolfe for rank-one matrix recovery without strong convexity.. Math. Program., 199 (1): 87-121 (мая 2023)Online Principal Components Analysis., , , и . SODA, стр. 887-901. SIAM, (2015)New Projection-free Algorithms for Online Convex Optimization with Adaptive Regret Guarantees., и . COLT, том 178 из Proceedings of Machine Learning Research, стр. 2326-2359. PMLR, (2022)Frank-Wolfe with a Nearest Extreme Point Oracle., и . COLT, том 134 из Proceedings of Machine Learning Research, стр. 2103-2132. PMLR, (2021)Frank-Wolfe-based Algorithms for Approximating Tyler's M-estimator., и . NeurIPS, (2022)Revisiting Frank-Wolfe for Polytopes: Strict Complementarity and Sparsity.. NeurIPS, (2020)A Linearly Convergent Variant of the Conditional Gradient Algorithm under Strong Convexity, with Applications to Online and Stochastic Optimization., и . SIAM J. Optim., 26 (3): 1493-1528 (2016)Improved Regret Bounds for Projection-free Bandit Convex Optimization., и . AISTATS, том 108 из Proceedings of Machine Learning Research, стр. 2196-2206. PMLR, (2020)