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Generating and Characterizing Scenarios for Safety Testing of Autonomous Vehicles


Mar 12, 2021
Zahra Ghodsi, Siva Kumar Sastry Hari, Iuri Frosio, Timothy Tsai, Alejandro Troccoli, Stephen W. Keckler, Siddharth Garg, Anima Anandkumar


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DeepReDuce: ReLU Reduction for Fast Private Inference


Mar 02, 2021
Nandan Kumar Jha, Zahra Ghodsi, Siddharth Garg, Brandon Reagen

* 12 pages, 5 Figures 

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Bait and Switch: Online Training Data Poisoning of Autonomous Driving Systems


Nov 08, 2020
Naman Patel, Prashanth Krishnamurthy, Siddharth Garg, Farshad Khorrami

* To appear in the NeurIPS 2020 Workshop on Dataset Curation and Security 

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Detecting Backdoors in Neural Networks Using Novel Feature-Based Anomaly Detection


Nov 04, 2020
Hao Fu, Akshaj Kumar Veldanda, Prashanth Krishnamurthy, Siddharth Garg, Farshad Khorrami


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On Evaluating Neural Network Backdoor Defenses


Oct 23, 2020
Akshaj Veldanda, Siddharth Garg


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Subverting Privacy-Preserving GANs: Hiding Secrets in Sanitized Images


Sep 19, 2020
Kang Liu, Benjamin Tan, Siddharth Garg


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Adversarially Robust Learning via Entropic Regularization


Aug 27, 2020
Gauri Jagatap, Animesh Basak Chowdhury, Siddharth Garg, Chinmay Hegde


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CryptoNAS: Private Inference on a ReLU Budget


Jun 15, 2020
Zahra Ghodsi, Akshaj Veldanda, Brandon Reagen, Siddharth Garg


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Bias Busters: Robustifying DL-based Lithographic Hotspot Detectors Against Backdooring Attacks


Apr 26, 2020
Kang Liu, Benjamin Tan, Gaurav Rajavendra Reddy, Siddharth Garg, Yiorgos Makris, Ramesh Karri


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NNoculation: Broad Spectrum and Targeted Treatment of Backdoored DNNs


Feb 19, 2020
Akshaj Kumar Veldanda, Kang Liu, Benjamin Tan, Prashanth Krishnamurthy, Farshad Khorrami, Ramesh Karri, Brendan Dolan-Gavitt, Siddharth Garg


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Are Adversarial Perturbations a Showstopper for ML-Based CAD? A Case Study on CNN-Based Lithographic Hotspot Detection


Jun 25, 2019
Kang Liu, Haoyu Yang, Yuzhe Ma, Benjamin Tan, Bei Yu, Evangeline F. Y. Young, Ramesh Karri, Siddharth Garg


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FATE: Fast and Accurate Timing Error Prediction Framework for Low Power DNN Accelerator Design


Jul 02, 2018
Jeff Zhang, Siddharth Garg

* To appear at IEEE/ACM International Conference On Computer Aided Design 2018 

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Fine-Pruning: Defending Against Backdooring Attacks on Deep Neural Networks


May 30, 2018
Kang Liu, Brendan Dolan-Gavitt, Siddharth Garg


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ThUnderVolt: Enabling Aggressive Voltage Underscaling and Timing Error Resilience for Energy Efficient Deep Neural Network Accelerators


Mar 13, 2018
Jeff Zhang, Kartheek Rangineni, Zahra Ghodsi, Siddharth Garg


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Analyzing and Mitigating the Impact of Permanent Faults on a Systolic Array Based Neural Network Accelerator


Feb 17, 2018
Jeff Zhang, Tianyu Gu, Kanad Basu, Siddharth Garg

* To appear at IEEE VLSI Test Symposium 2018 

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BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain


Aug 22, 2017
Tianyu Gu, Brendan Dolan-Gavitt, Siddharth Garg


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SafetyNets: Verifiable Execution of Deep Neural Networks on an Untrusted Cloud


Jun 30, 2017
Zahra Ghodsi, Tianyu Gu, Siddharth Garg


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