Search Results for author: Gong Su

Found 3 papers, 3 papers with code

ScaleFL: Resource-Adaptive Federated Learning With Heterogeneous Clients

1 code implementation CVPR 2023 Fatih Ilhan, Gong Su, Ling Liu

In most FL approaches, all edge clients are assumed to have sufficient computation capabilities to participate in the learning of a deep neural network (DNN) model.

Federated Learning SST-2 +1

Gradient-Leakage Resilient Federated Learning

1 code implementation2 Jul 2021 Wenqi Wei, Ling Liu, Yanzhao Wu, Gong Su, Arun Iyengar

This paper presents a gradient leakage resilient approach to privacy-preserving federated learning with per training example-based client differential privacy, coined as Fed-CDP.

Federated Learning Privacy Preserving

Compiling ONNX Neural Network Models Using MLIR

1 code implementation19 Aug 2020 Tian Jin, Gheorghe-Teodor Bercea, Tung D. Le, Tong Chen, Gong Su, Haruki Imai, Yasushi Negishi, Anh Leu, Kevin O'Brien, Kiyokuni Kawachiya, Alexandre E. Eichenberger

Deep neural network models are becoming increasingly popular and have been used in various tasks such as computer vision, speech recognition, and natural language processing.

speech-recognition Speech Recognition

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