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Robust and Active Learning for Deep Neural Network Regression


Jul 28, 2021
Xi Li, George Kesidis, David J. Miller, Maxime Bergeron, Ryan Ferguson, Vladimir Lucic


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A BIC based Mixture Model Defense against Data Poisoning Attacks on Classifiers


May 28, 2021
Xi Li, David J. Miller, Zhen Xiang, George Kesidis


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Anomaly Detection of Test-Time Evasion Attacks using Class-conditional Generative Adversarial Networks


May 21, 2021
Hang Wang, David J. Miller, George Kesidis


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L-RED: Efficient Post-Training Detection of Imperceptible Backdoor Attacks without Access to the Training Set


Oct 21, 2020
Zhen Xiang, David J. Miller, George Kesidis


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Reverse Engineering Imperceptible Backdoor Attacks on Deep Neural Networks for Detection and Training Set Cleansing


Oct 15, 2020
Zhen Xiang, David J. Miller, George Kesidis


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Revealing Perceptible Backdoors, without the Training Set, via the Maximum Achievable Misclassification Fraction Statistic


Nov 18, 2019
Zhen Xiang, David J. Miller, George Kesidis


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Notes on Lipschitz Margin, Lipschitz Margin Training, and Lipschitz Margin p-Values for Deep Neural Network Classifiers


Oct 15, 2019
George Kesidis, David J. Miller


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Revealing Backdoors, Post-Training, in DNN Classifiers via Novel Inference on Optimized Perturbations Inducing Group Misclassification


Aug 27, 2019
Zhen Xiang, David J. Miller, George Kesidis


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Adversarial Learning in Statistical Classification: A Comprehensive Review of Defenses Against Attacks


May 13, 2019
David J. Miller, Zhen Xiang, George Kesidis


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A Mixture Model Based Defense for Data Poisoning Attacks Against Naive Bayes Spam Filters


Oct 31, 2018
David J. Miller, Xinyi Hu, Zhen Xiang, George Kesidis


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When Not to Classify: Anomaly Detection of Attacks (ADA) on DNN Classifiers at Test Time


Jun 28, 2018
David J. Miller, Yulia Wang, George Kesidis


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ATD: Anomalous Topic Discovery in High Dimensional Discrete Data


May 20, 2016
Hossein Soleimani, David J. Miller


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Convex Analysis of Mixtures for Separating Non-negative Well-grounded Sources


Dec 10, 2015
Yitan Zhu, Niya Wang, David J. Miller, Yue Wang

* 15 pages, 9 figures, 2 tables 

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Detecting Clusters of Anomalies on Low-Dimensional Feature Subsets with Application to Network Traffic Flow Data


Jun 10, 2015
Zhicong Qiu, David J. Miller, George Kesidis


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Parsimonious Topic Models with Salient Word Discovery


Sep 11, 2014
Hossein Soleimani, David J. Miller

* IEEE Transaction on Knowledge and Data Engineering, 27 (2015) 824-837 

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