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Showing 2022 · cs.LGShow all
3 papers · 2 filters
cs.LG2022★ 5 cited
Distributed Adversarial Training to Robustify Deep Neural Networks at Scale
Gaoyuan Zhang, Songtao Lu, Yihua Zhang +7
Current deep neural networks (DNNs) are vulnerable to adversarial attacks, where adversarial perturbations to the inputs can change or manipulate classification. To defend against…
cs.LG2022★ 7 cited
Towards cost-effective and resource-aware aggregation at Edge for Federated Learning
Ahmad Faraz Khan, Yuze Li, Xinran Wang +5
Federated Learning (FL) is a machine learning approach that addresses privacy and data transfer costs by computing data at the source. It's particularly popular for Edge and IoT ap…
cs.LG2022★ 2 cited
NCVX: A User-Friendly and Scalable Package for Nonconvex Optimization in Machine Learning
Buyun Liang, Tim Mitchell, Ju Sun
Optimizing nonconvex (NCVX) problems, especially nonsmooth and constrained ones, is an essential part of machine learning. However, it can be hard to reliably solve such problems w…