Chen-Yu Ho

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Marco CaniniKAUSTEmail yang diverifikasi di kaust.edu.sa
Panos KalnisProfessor of Computer Science, King Abdullah University of Science and Technology (KAUST)Email yang diverifikasi di kaust.edu.sa
Peter RichtarikProfessor, KAUSTEmail yang diverifikasi di kaust.edu.sa
Amedeo SapioNVIDIAEmail yang diverifikasi di nvidia.com
Aritra DuttaAssistant Professor, University of Central FloridaEmail yang diverifikasi di ucf.edu
El Houcine BergouUM6PEmail yang diverifikasi di um6p.ma
Dan R. K. PortsMicrosoft ResearchEmail yang diverifikasi di cs.washington.edu
Arvind KrishnamurthyShort-Dooley Professor, Univ. of WashingtonEmail yang diverifikasi di cs.washington.edu
Changhoon (Chang) KimGoogleEmail yang diverifikasi di google.com
Masoud MoshrefPrincipal Software & System ArchitectEmail yang diverifikasi di nvidia.com
Jacob NelsonMicrosoft ResearchEmail yang diverifikasi di microsoft.com
Hang XuKing Abdullah University of Science and TechnologyEmail yang diverifikasi di kaust.edu.sa
Konstantinos KaratsenidisDepartment of Computer Science, Boston UniversityEmail yang diverifikasi di bu.edu
Pantelis PapageorgiouAnthropocene BioEmail yang diverifikasi di anthropocene.bio
Samuel HorvathMohamed bin Zayed University of Artificial Intelligence (MBZUAI)Email yang diverifikasi di mbzuai.ac.ae
Muhammad BilalSenior Engineering Manager @ UnbabelEmail yang diverifikasi di unbabel.com
Ahmed M. A. SayedAssoc. Prof., Queen Mary University of LondonEmail yang diverifikasi di qmul.ac.uk

Ikuti

Chen-Yu Ho

ByteDance Inc.

Email yang diverifikasi di bytedance.com - Beranda

Distributed Systems Machine Learning Federated Learning


Judul Urutkan menurut kutipan Urutkan menurut tahun Urutkan menurut judul	Dikutip oleh Dikutip oleh	Tahun
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	501	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	191*	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	185	2022
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	105	2021
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	101	2020
A Comprehensive Empirical Study of Heterogeneity in Federated Learning AM Abdelmoniem, CY Ho, P Papageorgiou, M Canini IEEE Internet of Things Journal, 2023	96*	2023
Tackling the Communication Bottlenecks of Distributed Deep Learning Training Workloads CY Ho		2023

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