2 citations · 2 across the 2 of their papers we have counts for
3 papers
cs.LG2023
Accelerated Gradient Algorithms with Adaptive Subspace Search for Instance-Faster Optimization
Yuanshi Liu, Hanzhen Zhao, Yang Xu +2
Gradient-based minimax optimal algorithms have greatly promoted the development of continuous optimization and machine learning. One seminal work due to Yurii Nesterov [Nes83a] est…
cs.LG2023
CORE: Common Random Reconstruction for Distributed Optimization with Provable Low Communication Complexity
Pengyun Yue, Hanzhen Zhao, Cong Fang +4
With distributed machine learning being a prominent technique for large-scale machine learning tasks, communication complexity has become a major bottleneck for speeding up trainin…
math.OC2023★ 2 cited
Zeroth-order Optimization with Weak Dimension Dependency
Pengyun Yue, Long Yang, Cong Fang +1
Zeroth-order optimization is a fundamental research topic that has been a focus of various learning tasks, such as black-box adversarial attacks, bandits, and reinforcement learnin…