When millions click at once, auto-scaling won’t save you — smart systems survive with load shedding, isolation and lots of ...
From autonomous cars to video games, reinforcement learning (machine learning through interaction with environments) can have ...
Abstract: We propose to apply optical circuit switching to enable dynamic AllReduce reconfiguration for accelerating distributed machine learning. With simulated annealing-based optimization, the ...
Abstract: As a new distributed machine learning framework, vertical federated learning (VFL) has been widely applied in the industry. However, recent studies have demonstrated that VFL faces serious ...
Now they’re being clogged with AI slop. Scientific publishing has always had its plumbing problems. Even before ChatGPT, ...
Federated learning leverages data across institutions to improve clinical discovery while complying with data-sharing restrictions and protecting patient privacy. This paper provides a gentle ...
CloudMesh is a UW SE capstone project that aims to create a decentralized, P2P approach to distributed machine learning training.
MLCommons selected four Georgia Tech students to participate in its 2025 Rising Stars cohort. A two-day Rising Stars workshop was held at Meta’s headquarters in May, where the participants showcased ...
ABSTRACT: Doping is an issue associated with elite sports as athletes attempt to enhance their performance to gain an edge over other athletes. However, the prevalence of doping is continuously ...
FedERA is a modular and fully customizable open-source FL framework, aiming to address these issues by offering comprehensive support for heterogeneous edge devices and incorporating both standalone ...
The new capabilities are designed to enable enterprises in regulated industries to securely build and refine machine learning models using shared data without compromising privacy. AWS has rolled out ...
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