Yu Gan
Orcid: 0000-0003-2697-9950Affiliations:
- Cornell University, Ithaca, NY, USA
According to our database1,
Yu Gan
authored at least 22 papers
between 2015 and 2024.
Collaborative distances:
Collaborative distances:
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Bibliography
2024
2023
Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2023
Sleuth: A Trace-Based Root Cause Analysis System for Large-Scale Microservices with Graph Neural Networks.
Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2023
2022
ACM SIGOPS Oper. Syst. Rev., 2022
IEEE Micro, 2022
CoRR, 2022
2021
CoRR, 2021
Sage: Using Unsupervised Learning for Scalable Performance Debugging in Microservices.
CoRR, 2021
Proceedings of the ASPLOS '21: 26th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2021
2020
Unveiling the Hardware and Software Implications of Microservices in Cloud and Edge Systems.
IEEE Micro, 2020
2019
Leveraging Deep Learning to Improve Performance Predictability in Cloud Microservices with Seer.
ACM SIGOPS Oper. Syst. Rev., 2019
Leveraging Deep Learning to Improve the Performance Predictability of Cloud Microservices.
CoRR, 2019
Proceedings of the IEEE International Symposium on Performance Analysis of Systems and Software, 2019
Seer: Leveraging Big Data to Navigate the Complexity of Performance Debugging in Cloud Microservices.
Proceedings of the Twenty-Fourth International Conference on Architectural Support for Programming Languages and Operating Systems, 2019
An Open-Source Benchmark Suite for Microservices and Their Hardware-Software Implications for Cloud & Edge Systems.
Proceedings of the Twenty-Fourth International Conference on Architectural Support for Programming Languages and Operating Systems, 2019
2018
IEEE Comput. Archit. Lett., 2018
Proceedings of the 10th USENIX Workshop on Hot Topics in Cloud Computing, 2018
2016
IEEE Trans. Commun., 2016
2015
Incentive Attack Prevention for Collaborative Spectrum Sensing: A Peer-Prediction Method.
Proceedings of the 2015 IEEE Global Communications Conference, 2015