Tag Archives: conference

Understanding the Resilience of Neural Network Ensembles against Faulty Training Data

Posted on October 22, 2021 by | Comments Off on Understanding the Resilience of Neural Network Ensembles against Faulty Training Data

Abraham Chan, Niranjhana Narayananan, Arpan Gujarati, Karthik Pattabiraman, and Sathish Gopalakrishnan, IEEE International Symposium on Quality, Reliability and Security (QRS), 2021. Full paper (Acceptance Rate: 25.1%) [ PDF | Talk | Video ] Best Paper Award (1 of 3)

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OneOS: Middleware for Running Edge Computing Applications as Distributed POSIX Pipelines

Posted on September 4, 2021 by | Comments Off on OneOS: Middleware for Running Edge Computing Applications as Distributed POSIX Pipelines

Kumseok Jung, Julien Gascon-Samson, and Karthik Pattabiraman, ACM/IEEE Symposium on Edge Computing (SEC), 2021 (Acceptance Rate: 27%) [ PDF | Talk ] (code, demo video). Best Demo Award (one award given)
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MIRAGE: Machine Learning-based Modeling of Identical Replicas of the Jetson AGX Embedded Platform

Posted on September 4, 2021 by | Comments Off on MIRAGE: Machine Learning-based Modeling of Identical Replicas of the Jetson AGX Embedded Platform

Hazem A. Abdelhafez, Hassan Halawa, Mohamed Ahmed, Karthik Pattabiraman, and Matei Ripeanu. ACM/IEEE Symposium on Edge Computing (SEC), 2021 (Acceptance Rate: 27%). [ PDF | Talk ]
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Are you for Real? Authentication in Dynamic IoT Systems

Posted on September 2, 2021 by | Comments Off on Are you for Real? Authentication in Dynamic IoT Systems

Mehdi Karimibiuki, Karthik Pattabiraman, and Andre Ivanov, IEEE International Symposium on Pacific Rim Dependable Computing (PRDC), 2021. (Acceptance Rate: 43%) [ PDF | Talk ]
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PID-Piper: Recovering Robotic Vehicles from Physical Attacks

Posted on March 10, 2021 by | Comments Off on PID-Piper: Recovering Robotic Vehicles from Physical Attacks

Pritam Dash, Guanpeng Li, Zitao Chen, Mehdi Karimibiuki, and Karthik Pattabiraman, IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), 2021. (Acceptance Rate: 16.5%). [ PDF | Talk, Talk Video ] (Code, PID-Piper Videos) Best Paper Award (1 of nearly 300 submissions).
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A Low-cost Fault Corrector for Deep Neural Networks through Range Restriction

Posted on March 10, 2021 by | Comments Off on A Low-cost Fault Corrector for Deep Neural Networks through Range Restriction

Zitao Chen, Guanpeng Li, and Karthik Pattabiraman, IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), 2021. (Acceptance Rate: 16.5%). [ PDF | Talk , Video] (arXIV, code) Best Paper Award Runner up (1 of 2 among nearly 300 submissions). Incorporated into Intel’s OpenVino2 Framework (More details, Documentation).
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How Far Have We Come in Detecting Anomalies in Distributed Systems? An Empirical Study with a Statement-level Fault Injection Method

Posted on August 14, 2020 by | Comments Off on How Far Have We Come in Detecting Anomalies in Distributed Systems? An Empirical Study with a Statement-level Fault Injection Method

Yong Yang, Yifan Yu, Karthik Pattabiraman, Long Wang, Ying Li, IEEE International Symposium on Software Reliability Engineering (ISSRE), 2020. (Acceptance Rate: 26%). [ PDF | Talk ] (Code)
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TensorFI: A Flexible Fault Injection Framework for TensorFlow Applications

Posted on August 14, 2020 by | Comments Off on TensorFI: A Flexible Fault Injection Framework for TensorFlow Applications

Zitao Chen, Niranjhana Narayanan, Bo Fang, Guanpeng Li, Karthik Pattabiraman, and Nathan DeBardeleben, IEEE International Symposium on Software Reliability Engineering (ISSRE), 2020. (Acceptance Rate: 26%) [ PDF | Talk ] (Code)
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GPU-TRIDENT: Efficient Modeling of Error Propagation in GPU Programs

Posted on June 30, 2020 by | Comments Off on GPU-TRIDENT: Efficient Modeling of Error Propagation in GPU Programs

Abdul Rehman Anwer, Guanpeng Li, Karthik Pattabiraman, Michael Sullivan, Timothy Tsai and Siva Hari, ACM International Conference on High-Performance Computing, Networking, Storage, and Analyzis (SC), 2020 (Acceptance Rate: 25.1%) [PDF | Talk] (Code)
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How Effective are Smart Contract Static Analysis Tools ? Evaluating Smart Contract Static Analysis Tools Using Bug Injection

Posted on May 22, 2020 by | Comments Off on How Effective are Smart Contract Static Analysis Tools ? Evaluating Smart Contract Static Analysis Tools Using Bug Injection

Asem Ghaleb and Karthik Pattabiraman, Proceedings of the ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA), 2020. (Acceptance Rate: 26%) [PDF | Talk] (DataSet, Code – Artifacts Functional Badge)
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