4 papers
On the Trustworthiness of Generative Foundation Models: Guideline, Assessment, and Perspective
Yue Huang, Chujie Gao, Siyuan Wu +63
Generative Foundation Models (GenFMs) have emerged as transformative tools. However, their widespread adoption raises critical concerns regarding trustworthiness across dimensions.…
Coresets for Clustering Under Stochastic Noise
Lingxiao Huang, Zhize Li, Nisheeth K. Vishnoi +2
We study the problem of constructing coresets for -clustering when the input dataset is corrupted by stochastic noise drawn from a known distribution. In this setting, eval…
EF21 with Bells & Whistles: Six Algorithmic Extensions of Modern Error Feedback
Ilyas Fatkhullin, Igor Sokolov, Eduard Gorbunov +2
First proposed by Seide (2014) as a heuristic, error feedback (EF) is a very popular mechanism for enforcing convergence of distributed gradient-based optimization methods enhanced…
The Effectiveness of Local Updates for Decentralized Learning under Data Heterogeneity
Tongle Wu, Zhize Li, Ying Sun
We revisit two fundamental decentralized optimization methods, Decentralized Gradient Tracking (DGT) and Decentralized Gradient Descent (DGD), with multiple local updates. We consi…