Author of the publication

The Fault in Our Data Stars: Studying Mitigation Techniques against Faulty Training Data in Machine Learning Applications.

, , , and . DSN, page 163-171. IEEE, (2022)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

No persons found for author name Gujarati, Arpan
add a person with the name Gujarati, Arpan
 

Other publications of authors with the same name

The Fault in Our Data Stars: Studying Mitigation Techniques against Faulty Training Data in Machine Learning Applications., , , and . DSN, page 163-171. IEEE, (2022)Correspondence article: a correction of the reduction-based schedulability analysis for APA scheduling., , , and . Real Time Syst., 55 (1): 136-143 (2019)Towards Ültra-Reliable" CPS: Reliability Analysis of Distributed Real-Time Systems.. Kaiserslautern University of Technology, Germany, (2020)Tableau: a high-throughput and predictable VM scheduler for high-density workloads., , and . EuroSys, page 28:1-28:16. ACM, (2018)When Is CAN the Weakest Link? A Bound on Failures-in-Time in CAN-Based Real-Time Systems., and . RTSS, page 249-260. IEEE Computer Society, (2015)Real-Time Replica Consistency over Ethernet with Reliability Bounds., , and . RTAS, page 376-389. IEEE, (2020)Understanding the Resilience of Neural Network Ensembles against Faulty Training Data., , , , and . QRS, page 1100-1111. IEEE, (2021)Swayam: distributed autoscaling to meet SLAs of machine learning inference services with resource efficiency., , , , and . Middleware, page 109-120. ACM, (2017)Towards Building Resilient Ensembles against Training Data Faults., , , and . DSN Workshops, page 68-69. IEEE, (2022)Evaluating the Effect of Common Annotation Faults on Object Detection Techniques., , , and . ISSRE, page 474-485. IEEE, (2023)