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Promoting High Diversity Ensemble Learning with EnsembleBench
Ensemble learning is gaining renewed interests in recent years. This pap...
10/20/2020 ∙ by Yanzhao Wu, et al. ∙
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Efficient Orchestration of Host and Remote Shared Memory for Memory Intensive Workloads
Since very few contributions to the development of an unified memory orc...
08/03/2020 ∙ by Juhyun Bae, et al. ∙
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Understanding Object Detection Through An Adversarial Lens
Deep neural networks based object detection models have revolutionized c...
07/11/2020 ∙ by Ka-Ho Chow, et al. ∙
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A Framework for Evaluating Gradient Leakage Attacks in Federated Learning
Federated learning (FL) is an emerging distributed machine learning fram...
04/22/2020 ∙ by Wenqi Wei, et al. ∙
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TOG: Targeted Adversarial Objectness Gradient Attacks on Real-time Object Detection Systems
The rapid growth of real-time huge data capturing has pushed the deep le...
04/09/2020 ∙ by Ka-Ho Chow, et al. ∙
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Cross-Layer Strategic Ensemble Defense Against Adversarial Examples
Deep neural network (DNN) has demonstrated its success in multiple domai...
10/01/2019 ∙ by Wenqi Wei, et al. ∙
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Deep Neural Network Ensembles against Deception: Ensemble Diversity, Accuracy and Robustness
Ensemble learning is a methodology that integrates multiple DNN learners...
08/29/2019 ∙ by Ling Liu, et al. ∙
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Denoising and Verification Cross-Layer Ensemble Against Black-box Adversarial Attacks
Deep neural networks (DNNs) have demonstrated impressive performance on ...
08/21/2019 ∙ by Ka-Ho Chow, et al. ∙
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Demystifying Learning Rate Polices for High Accuracy Training of Deep Neural Networks
Learning Rate (LR) is an important hyper-parameter to tune for effective...
08/18/2019 ∙ by Yanzhao Wu, et al. ∙
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A Comparative Measurement Study of Deep Learning as a Service Framework
Big data powered Deep Learning (DL) and its applications have blossomed ...
10/29/2018 ∙ by Yanzhao Wu, et al. ∙
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