Interpretable Feedback for AutoML and a Proposal for Domain-customized AutoML for Networking-Reference-Cited by-同舟云学术

Interpretable Feedback for AutoML and a Proposal for Domain-customized AutoML for Networking

Published:2021-11-04 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Twentieth ACM Workshop on Hot Topics in Networks
language:
Short-container-title:

Author:

Arzani Behnaz¹,Hsieh Kevin¹,Chen Haoxian²

Affiliation:

1. Microsoft

2. University of Pennsylvania

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3484266.3487373

Reference57 articles.

1. The good the bad and the ugly of ml for networked systems. https://www.microsoft.com/en-us/research/video/the-good-the-bad-and-the-ugly-of-ml-for-networked-systems/. The good the bad and the ugly of ml for networked systems. https://www.microsoft.com/en-us/research/video/the-good-the-bad-and-the-ugly-of-ml-for-networked-systems/.

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Efficient Attack Detection with Multi-Latency Neural Models on Heterogeneous Network Devices;2023 IEEE 31st International Conference on Network Protocols (ICNP);2023-10-10

2. Dynamic sales prediction with auto-learning and elastic-adjustment mechanism for inventory optimization;Information Systems;2023-10

3. LEAF: Navigating Concept Drift in Cellular Networks;Proceedings of the ACM on Networking;2023-09-28

4. GGFAST: Automating Generation of Flexible Network Traffic Classifiers;Proceedings of the ACM SIGCOMM 2023 Conference;2023-09

5. AutoML in The Wild: Obstacles, Workarounds, and Expectations;Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems;2023-04-19