6 citations · 14 across the 8 of their papers we have counts for
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cs.AR2022★ 2 cited
DiVa: An Accelerator for Differentially Private Machine Learning
Beomsik Park, Ranggi Hwang, Dongho Yoon +2
The widespread deployment of machine learning (ML) is raising serious concerns on protecting the privacy of users who contributed to the collection of training data. Differential p…
cs.AR2022★ 1 cited
GROW: A Row-Stationary Sparse-Dense GEMM Accelerator for Memory-Efficient Graph Convolutional Neural Networks
Ranggi Hwang, Minhoo Kang, Jiwon Lee +3
Graph convolutional neural networks (GCNs) have emerged as a key technology in various application domains where the input data is relational. A unique property of GCNs is that its…