396 citations · 1.6k across the 95 of their papers we have counts for
Showing 2021 · cs.LGShow all
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cs.LG2021★ 11 cited
Splitfed learning without client-side synchronization: Analyzing client-side split network portion size to overall performance
Praveen Joshi, Chandra Thapa, Seyit Camtepe +3
Federated Learning (FL), Split Learning (SL), and SplitFed Learning (SFL) are three recent developments in distributed machine learning that are gaining attention due to their abil…
cs.LG2021★ 1 cited
Evaluation and Optimization of Distributed Machine Learning Techniques for Internet of Things
Yansong Gao, Minki Kim, Chandra Thapa +5
Federated learning (FL) and split learning (SL) are state-of-the-art distributed machine learning techniques to enable machine learning training without accessing raw data on clien…
cs.LG2021★ 2 cited
Understanding and Achieving Efficient Robustness with Adversarial Supervised Contrastive Learning
Anh Bui, Trung Le, He Zhao +3
Contrastive learning (CL) has recently emerged as an effective approach to learning representation in a range of downstream tasks. Central to this approach is the selection of posi…