MUSE: Multi-Tenant Model Serving With Seamless Model Updates

Ali Nemati5 days ago24 sec read7 views

MUSE is a new framework introduced for multi-tenant environments that allows seamless updates to machine learning models without disrupting client decision-making processes. By decoupling model scores from decision thresholds and optimizing infrastructure reuse, MUSE significantly reduces recalibration time and human coordination efforts, leading to faster deployment and improved resilience against fraud attacks.

Read the full article at arXiv cs.LG (ML)

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