Chen-Yu Ho

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Marco CaniniKAUSTVerified email at kaust.edu.sa
Panos KalnisProfessor of Computer Science, King Abdullah University of Science and Technology (KAUST)Verified email at kaust.edu.sa
Peter RichtarikProfessor, KAUSTVerified email at kaust.edu.sa
Amedeo SapioAWSVerified email at amazon.com
Aritra DuttaAssistant Professor, University of Central FloridaVerified email at ucf.edu
El Houcine BergouUM6PVerified email at um6p.ma
Dan R. K. PortsMicrosoft ResearchVerified email at cs.washington.edu
Arvind KrishnamurthyShort-Dooley Professor, Univ. of WashingtonVerified email at cs.washington.edu
Changhoon (Chang) KimGoogleVerified email at google.com
Masoud MoshrefPrincipal Software & System ArchitectVerified email at nvidia.com
Jacob NelsonMicrosoft ResearchVerified email at microsoft.com
Hang XuKing Abdullah University of Science and TechnologyVerified email at kaust.edu.sa
Konstantinos KaratsenidisDepartment of Computer Science, Boston UniversityVerified email at bu.edu
Samuel HorvathMohamed bin Zayed University of Artificial Intelligence (MBZUAI)Verified email at mbzuai.ac.ae
Pantelis PapageorgiouMSc candidate in Advanced Computer Science at University of OxfordVerified email at cs.ox.ac.uk
Muhammad BilalSenior Engineering Manager @ UnbabelVerified email at unbabel.com
Ahmed M. A. SayedAssoc. Prof., Queen Mary University of LondonVerified email at qmul.ac.uk

Chen-Yu Ho

ByteDance Inc.

Verified email at bytedance.com - Homepage


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Scaling Distributed Machine Learning with In-Network Aggregation A Sapio, M Canini, CY Ho, J Nelson, P Kalnis, C Kim, A Krishnamurthy, ... Proceedings of the 18th USENIX Symposium on Networked Systems Design and …, 2021	467	2021
GRACE: A compressed communication framework for distributed machine learning H Xu, CY Ho, AM Abdelmoniem, A Dutta, EH Bergou, K Karatsenidis, ... 2021 IEEE 41st international conference on distributed computing systems …, 2021	174*	2021
Natural compression for distributed deep learning S Horvóth, CY Ho, L Horvath, AN Sahu, M Canini, P Richtárik Mathematical and Scientific Machine Learning, 129-141, 2022	172	2022
On the discrepancy between the theoretical analysis and practical implementations of compressed communication for distributed deep learning A Dutta, EH Bergou, AM Abdelmoniem, CY Ho, AN Sahu, M Canini, ... Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 3817-3824, 2020	97	2020
Efficient sparse collective communication and its application to accelerate distributed deep learning J Fei, CY Ho, AN Sahu, M Canini, A Sapio Proceedings of the 2021 ACM SIGCOMM 2021 Conference, 676-691, 2021	93	2021
A Comprehensive Empirical Study of Heterogeneity in Federated Learning AM Abdelmoniem, CY Ho, P Papageorgiou, M Canini IEEE Internet of Things Journal, 2023	78*	2023
Tackling the Communication Bottlenecks of Distributed Deep Learning Training Workloads CY Ho		2023

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