ALBADross: Active Learning Based Anomaly Diagnosis for Production HPC Systems.
Abstract not provided.
Aksar, Burak↗
Engineering topics
Aksar, Burak
Publications and source records attributed to Aksar, Burak.
Using Monitoring Data to Improve HPC Performance via Network-Data-Driven Allocation.
Abstract not provided.
Zhang, Yijia↗
Using Monitoring Data to Improve HPC Performance via Network-Data-Driven Allocation.
Abstract not provided.
Zhang, Yijia↗
E2EWatch: End-to-end Anomaly Diagnosis Framework for Production HPC Systems.
Abstract not provided.
Aksar, Burak↗
E2EWatch: End-to-end Anomaly Diagnosis Framework for Production HPC Systems.
Abstract not provided.
Aksar, Burak↗
CoMTE: Counterfactual Explanations for Supervised Machine Learning Frameworks on Multivariate Time Series Data
CoMTE is a novel explainability technique that provides counterfactual explanations for supervised machine learning frameworks on multivariate time series data. CoMTE outperforms state-of-the-art explainability methods on several different machine learning frameworks and data sets in comprehensibility and robustness. CoMTE can be used to debug machine learning frameworks and gain a better understanding of the underlying multivariate time series data. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-1686 O
Leung, VitusJ.↗
Proctor: A Semi-Supervised Performance Anomaly Diagnosis Framework for Production HPC Systems.
Abstract not provided.
Aksar, Burak↗