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05/23/2023
Mitigating the Performance Impact of Network Failures in Public Clouds
Some faults in data center networks require hours to days to repair beca...
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05/22/2023
Rethinking Machine Learning Collective Communication as a Multi-Commodity Flow Problem
We show communication schedulers' recent work proposed for ML collective...
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02/02/2022
FedSpace: An Efficient Federated Learning Framework at Satellites and Ground Stations
Large-scale deployments of low Earth orbit (LEO) satellites collect mass...
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10/11/2021
Towards a Cost vs. Quality Sweet Spot for Monitoring Networks
Continuously monitoring a wide variety of performance and fault metrics ...
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02/22/2021
Interpret-able feedback for AutoML systems
Automated machine learning (AutoML) systems aim to enable training machi...
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04/24/2020
Towards A Domain-Customized Automated Machine Learning Framework For Networks and Systems
Clouds gather a vast volume of telemetry from their networked systems wh...
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12/01/2018
Sunstar: A Cost-effective Multi-Server Solution for Reliable Video Delivery
In spite of much progress and many advances, cost-effective, high-qualit...
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02/20/2018