Sangyoon Oh 0001 - researchr alias

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Viewing Publication 1 - 8 from 8

2023

Can hierarchical client clustering mitigate the data heterogeneity effect in federated learning?Seungjun Lee, Miri Yu, Daegun Yoon, Sangyoon Oh 0001. ipps 2023: 799-808 [doi]

User Preference-Based Hierarchical Offloading for Collaborative Cloud-Edge ComputingShujuan Tian, Chi Chang, Saiqin Long, Sangyoon Oh 0001, Zhetao Li, Jun Long. tsc, 16(1):684-697, January - February 2023. [doi]

Crossover-SGD: A gossip-based communication in distributed deep learning for alleviating large mini-batch problem and enhancing scalabilitySangho Yeo, Minho Bae, Minjoong Jeong, Oh-Kyoung Kwon, Sangyoon Oh 0001. concurrency, 35(15), 2023. [doi]

MiCRO: Near-Zero Cost Gradient Sparsification for Scaling and Accelerating Distributed DNN TrainingDaegun Yoon, Sangyoon Oh 0001. hipc 2023: 87-96 [doi]

DEFT: Exploiting Gradient Norm Difference between Model Layers for Scalable Gradient SparsificationDaegun Yoon, Sangyoon Oh 0001. icpp 2023: 746-755 [doi]

WAVE: designing a heuristics-based three-way breadth-first search on GPUsDaegun Yoon, Minjoong Jeong, Sangyoon Oh 0001. tjs, 79(6):6889-6917, April 2023. [doi]

SAGE: toward on-the-fly gradient compression ratio scalingDaegun Yoon, Minjoong Jeong, Sangyoon Oh 0001. tjs, 79(10):11387-11409, July 2023. [doi]

Addressing Client Heterogeneity in Synchronous Federated Learning: The CHAFL ApproachMiri Yu, Oh-Kyoung Kwon, Sangyoon Oh 0001. icpads 2023: 2804-2805 [doi]

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