Itron and Toumetis Team Up with Southern California Utility to Reduce Wildfire Risk and Improve Reliability by Preventing Outages and Shortening Restoration Time

Initial work includes data integration and measuring results over time, including prevented events, time-to-locate and time-to-restore metrics. Itron and Toumetis expect to use the results to guide a ...
IEEE

Accelerating Distributed Machine Learning with Allreduce Reconfiguration Based on Optical Circuit Switching

Abstract: We propose to apply optical circuit switching to enable dynamic AllReduce reconfiguration for accelerating distributed machine learning. With simulated annealing-based optimization, the ...
IEEE

General Test-Time Backdoor Detection in Split Neural Network-Based Vertical Federated Learning

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 ...

Science Is Drowning in AI Slop

Now they’re being clogged with AI slop. Scientific publishing has always had its plumbing problems. Even before ChatGPT, ...
Frontiers

Technical and legal aspects of federated learning in bioinformatics: applications, challenges and opportunities

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 ...
InfoWorld

AI and machine learning outside of Python

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.
GitHub

distributed-machine-learning

CloudMesh is a UW SE capstone project that aims to create a decentralized, P2P approach to distributed machine learning training.
cc.gatech.edu

Students Recognized for Machine Learning Research

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 ...
Scientific Research Publishing

Baligodugula, V.V. (2023) Unsupervised-Based Distributed Machine Learning for Efficient Data Clustering and Prediction.

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 ...
GitHub

distributed-machine-learning

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 ...
InfoWorld

AWS adds incremental and distributed training to Clean Rooms for scalable ML collaboration

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 ...