Chen-Yu Ho

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Marco CaniniKAUSTEmail verificata su kaust.edu.sa
Panos KalnisProfessor of Computer Science, King Abdullah University of Science and Technology (KAUST)Email verificata su kaust.edu.sa
Ahmed M. AbdelmoniemAssistant Professor, QMULEmail verificata su qmul.ac.uk
Peter RichtarikProfessor, KAUSTEmail verificata su kaust.edu.sa
Amedeo SapioAWSEmail verificata su amazon.com
Aritra DuttaAssistant Professor, University of Central FloridaEmail verificata su ucf.edu
El Houcine BergouUM6PEmail verificata su um6p.ma
Dan R. K. PortsMicrosoft ResearchEmail verificata su cs.washington.edu
Arvind KrishnamurthyShort-Dooley Professor, Univ. of WashingtonEmail verificata su cs.washington.edu
Changhoon (Chang) KimGoogleEmail verificata su google.com
Masoud MoshrefPrincipal Software & System ArchitectEmail verificata su nvidia.com
Jacob NelsonMicrosoft ResearchEmail verificata su microsoft.com
Samuel HorvathMohamed bin Zayed University of Artificial Intelligence (MBZUAI)Email verificata su mbzuai.ac.ae
Hang XuKing Abdullah University of Science and TechnologyEmail verificata su kaust.edu.sa
Konstantinos KaratsenidisDepartment of Computer Science, Boston UniversityEmail verificata su bu.edu
Pantelis PapageorgiouMSc candidate in Advanced Computer Science at University of OxfordEmail verificata su cs.ox.ac.uk
Muhammad BilalSenior Engineering Manager @ UnbabelEmail verificata su unbabel.com

Chen-Yu Ho

ByteDance Inc.

Email verificata su bytedance.com - Home page


Titolo Ordina per citazioni Ordina per anno Ordina per titolo	Citata da Citata da	Anno
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	369	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	153	2022
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	143*	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	88	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	69	2021
A Comprehensive Empirical Study of Heterogeneity in Federated Learning AM Abdelmoniem, CY Ho, P Papageorgiou, M Canini IEEE Internet of Things Journal, 2023	52*	2023
Tackling the Communication Bottlenecks of Distributed Deep Learning Training Workloads CY Ho		2023

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Articoli 1–7

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