16 citations · 31 across the 7 of their papers we have counts for
4 papers · 1 filter
Proximal Gradient Algorithm with Momentum and Flexible Parameter Restart for Nonconvex Optimization
Yi Zhou, Zhe Wang, Kaiyi Ji +2
Various types of parameter restart schemes have been proposed for accelerated gradient algorithms to facilitate their practical convergence in convex optimization. However, the con…
History-Gradient Aided Batch Size Adaptation for Variance Reduced Algorithms
Kaiyi Ji, Zhe Wang, Bowen Weng +3
Variance-reduced algorithms, although achieve great theoretical performance, can run slowly in practice due to the periodic gradient estimation with a large batch of data. Batch-si…
Momentum Schemes with Stochastic Variance Reduction for Nonconvex Composite Optimization
Yi Zhou, Zhe Wang, Kaiyi Ji +2
Two new stochastic variance-reduced algorithms named SARAH and SPIDER have been recently proposed, and SPIDER has been shown to achieve a near-optimal gradient oracle complexity fo…
SpiderBoost and Momentum: Faster Stochastic Variance Reduction Algorithms
Zhe Wang, Kaiyi Ji, Yi Zhou +2
SARAH and SPIDER are two recently developed stochastic variance-reduced algorithms, and SPIDER has been shown to achieve a near-optimal first-order oracle complexity in smooth nonc…