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EENet: Learning to Early Exit for Adaptive Inference


Jan 15, 2023
Fatih Ilhan, Ling Liu, Ka-Ho Chow, Wenqi Wei, Yanzhao Wu, Myungjin Lee, Ramana Kompella, Hugo Latapie, Gaowen Liu

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Promoting High Diversity Ensemble Learning with EnsembleBench


Oct 20, 2020
Yanzhao Wu, Ling Liu, Zhongwei Xie, Juhyun Bae, Ka-Ho Chow, Wenqi Wei

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Understanding Object Detection Through An Adversarial Lens


Jul 11, 2020
Ka-Ho Chow, Ling Liu, Mehmet Emre Gursoy, Stacey Truex, Wenqi Wei, Yanzhao Wu

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LDP-Fed: Federated Learning with Local Differential Privacy


Jun 05, 2020
Stacey Truex, Ling Liu, Ka-Ho Chow, Mehmet Emre Gursoy, Wenqi Wei

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A Framework for Evaluating Gradient Leakage Attacks in Federated Learning


Apr 23, 2020
Wenqi Wei, Ling Liu, Margaret Loper, Ka-Ho Chow, Mehmet Emre Gursoy, Stacey Truex, Yanzhao Wu

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TOG: Targeted Adversarial Objectness Gradient Attacks on Real-time Object Detection Systems


Apr 09, 2020
Ka-Ho Chow, Ling Liu, Mehmet Emre Gursoy, Stacey Truex, Wenqi Wei, Yanzhao Wu

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Cross-Layer Strategic Ensemble Defense Against Adversarial Examples


Oct 01, 2019
Wenqi Wei, Ling Liu, Margaret Loper, Ka-Ho Chow, Emre Gursoy, Stacey Truex, Yanzhao Wu

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* To appear in IEEE ICNC 2020 

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Deep Neural Network Ensembles against Deception: Ensemble Diversity, Accuracy and Robustness


Aug 29, 2019
Ling Liu, Wenqi Wei, Ka-Ho Chow, Margaret Loper, Emre Gursoy, Stacey Truex, Yanzhao Wu

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* To appear in IEEE MASS 2019 

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Denoising and Verification Cross-Layer Ensemble Against Black-box Adversarial Attacks


Aug 21, 2019
Ka-Ho Chow, Wenqi Wei, Yanzhao Wu, Ling Liu

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Demystifying Learning Rate Polices for High Accuracy Training of Deep Neural Networks


Aug 18, 2019
Yanzhao Wu, Ling Liu, Juhyun Bae, Ka-Ho Chow, Arun Iyengar, Calton Pu, Wenqi Wei, Lei Yu, Qi Zhang

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