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SANDS Lab

Chen-Yu Ho

Natural Compression for Distributed Deep Learning
Empirical Analysis of Federated Learning in Heterogeneous Environments
Efficient Sparse Collective Communication and its application to Accelerate Distributed Deep Learning
Compressed Communication for Distributed Deep Learning: Survey and Quantitative Evaluation
Scaling Distributed Machine Learning with In-Network Aggregation
On the Discrepancy between the Theoretical Analysis and Practical Implementations of Compressed Communication for Distributed Deep Learning