85 citations · 153 across the 10 of their papers we have counts for
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cs.LG2026★ 2 cited
Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems
Shuo Huai, Di Liu, Hao Kong +5
Federated Learning (FL) empowers multiple clients to collaboratively learn a model, enlarging the training data of each client for high accuracy while protecting data privacy. Howe…
cs.LG2026★ 8 cited
Latency-Constrained DNN Architecture Learning for Edge Systems using Zerorized Batch Normalization
Shuo Huai, Di Liu, Hao Kong +4
Deep learning applications have been widely adopted on edge devices, to mitigate the privacy and latency issues of accessing cloud servers. Deciding the number of neurons during th…
cs.LG2020★ 2 cited
Cost-effective Machine Learning Inference Offload for Edge Computing
Christian Makaya, Amalendu Iyer, Jonathan Salfity +2
Computing at the edge is increasingly important since a massive amount of data is generated. This poses challenges in transporting all that data to the remote data centers and clou…