3 citations · 9 across the 9 of their papers we have counts for
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cs.LG2022★ 2 cited
GlueFL: Reconciling Client Sampling and Model Masking for Bandwidth Efficient Federated Learning
Shiqi He, Qifan Yan, Feijie Wu +3
Federated learning (FL) is an effective technique to directly involve edge devices in machine learning training while preserving client privacy. However, the substantial communicat…
cs.LG2021
Auto-Split: A General Framework of Collaborative Edge-Cloud AI
Amin Banitalebi-Dehkordi, Naveen Vedula, Jian Pei +3
In many industry scale applications, large and resource consuming machine learning models reside in powerful cloud servers. At the same time, large amounts of input data are collec…
cs.LG2019
Exact and Consistent Interpretation of Piecewise Linear Models Hidden behind APIs: A Closed Form Solution
Zicun Cong, Lingyang Chu, Lanjun Wang +2
More and more AI services are provided through APIs on cloud where predictive models are hidden behind APIs. To build trust with users and reduce potential application risk, it is…