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cs.LG2025
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…
cs.LG2025
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…
cs.LG2024
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…