arXiv Machine Learning By Kaiqi Jiang, Karim El Husseini, Wenzhe Fan, Xinhua Zhang

Trading Utility for Dynamic Fairness in Multiple Resource Division with Sequential Demand

Read the original on arXiv Machine Learning →

arXiv:2606. 10472v1 Announce Type: cross Abstract: Dynamic multi-resource allocation is a central problem in shared computing environments, where users' demands arrive sequentially and resources must be distributed fairly without knowledge of future demands.

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arXiv Machine Learning
Jul 14

Quota Marketplace: Dynamic Pricing for Efficient Allocation of ML Training Resources

arXiv:2607. 09802v1 Announce Type: new Abstract: The escalating demand for Machine Learning (ML) training resources in recent years has resulted in a substantial gap between the high demand and the available supply.

By Balasubramanian Sivan, Renato Paes Leme, Mihai Tiuca, Ian McFarlane, Vasilis Gkatzelis, Nehal Mehta, Soheil Hassas Yeganeh, Vahab Mirrokni, Amin Vahdat