Chen-Yu Ho

Publication Activity (10 Years)

Years Active: 2019-2023
Publications (10 Years): 11

Top Topics

Top Venues

IEEE Internet Things J.

Publications

Ahmed M. Abdelmoniem, Chen-Yu Ho, Pantelis Papageorgiou, Marco Canini
A Comprehensive Empirical Study of Heterogeneity in Federated Learning. IEEE Internet Things J. 10 (16) (2023)
Samuel Horváth, Chen-Yu Ho, Ludovit Horvath, Atal Narayan Sahu, Marco Canini, Peter Richtárik
Natural Compression for Distributed Deep Learning. MSML (2022)
Ahmed M. Abdelmoniem, Chen-Yu Ho, Pantelis Papageorgiou, Marco Canini
Empirical analysis of federated learning in heterogeneous environments. EuroMLSys@EuroSys (2022)
Jiawei Fei, Chen-Yu Ho, Atal Narayan Sahu, Marco Canini, Amedeo Sapio
Efficient sparse collective communication and its application to accelerate distributed deep learning. SIGCOMM (2021)
Ahmed M. Abdelmoniem, Chen-Yu Ho, Pantelis Papageorgiou, Muhammad Bilal, Marco Canini
On the Impact of Device and Behavioral Heterogeneity in Federated Learning. CoRR (2021)
Amedeo Sapio, Marco Canini, Chen-Yu Ho, Jacob Nelson, Panos Kalnis, Changhoon Kim, Arvind Krishnamurthy, Masoud Moshref, Dan R. K. Ports, Peter Richtárik
Scaling Distributed Machine Learning with In-Network Aggregation. NSDI (2021)
Hang Xu, Chen-Yu Ho, Ahmed M. Abdelmoniem, Aritra Dutta, El Houcine Bergou, Konstantinos Karatsenidis, Marco Canini, Panos Kalnis
GRACE: A Compressed Communication Framework for Distributed Machine Learning. ICDCS (2021)
Aritra Dutta, El Houcine Bergou, Ahmed M. Abdelmoniem, Chen-Yu Ho, Atal Narayan Sahu, Marco Canini, Panos Kalnis
On the Discrepancy between the Theoretical Analysis and Practical Implementations of Compressed Communication for Distributed Deep Learning. AAAI (2020)
Amedeo Sapio, Marco Canini, Chen-Yu Ho, Jacob Nelson, Panos Kalnis, Changhoon Kim, Arvind Krishnamurthy, Masoud Moshref, Dan R. K. Ports, Peter Richtárik
Scaling Distributed Machine Learning with In-Network Aggregation. CoRR (2019)
Aritra Dutta, El Houcine Bergou, Ahmed M. Abdelmoniem, Chen-Yu Ho, Atal Narayan Sahu, Marco Canini, Panos Kalnis
On the Discrepancy between the Theoretical Analysis and Practical Implementations of Compressed Communication for Distributed Deep Learning. CoRR (2019)
Samuel Horvath, Chen-Yu Ho, Ludovit Horvath, Atal Narayan Sahu, Marco Canini, Peter Richtárik
Natural Compression for Distributed Deep Learning. CoRR (2019)