Tech Xplore

New federated learning algorithm enables private, robust, and fast AI development

Three heads are better than one. Versions of this proverb are found worldwide and throughout history. Yet in the race to ...

Fuzheng Liu Examines Transformer-XL Modeling of E-Commerce User Behavior and Real-Time Behavioral Analysis

XL, dynamic interest modeling, and distributed stream computing to analyze large-scale e-commerce user behavior. By improving long-sequence prediction, real-time processing, and behavioral clustering, ...

Study compares machine learning models of raindrop formation

Raindrops form inside clouds when tiny particles of water collide and stick together, forming larger droplets that eventually ...
The Next Web

Entire launches a distributed Git network built for AI coding agents

Entire, founded by former GitHub CEO Thomas Dohmke, has launched a preview of a distributed Git network that mirrors GitHub repos across regions for AI agents.
Blockonomi

5 Leading AI Cryptocurrency Projects Shaping 2026: TAO, NEAR, and RENDER in Focus

Leading AI Cryptocurrency Tokens for 2025. The intersection of artificial intelligence and blockchain technology is ...
Modern Distribution Management

Lantern Raises $7M to Scale AI Forecasting Platform for Distributors

The San Francisco-based startup said its seed funding will support hiring, product development and continued expansion of its ...
RMD Open

Development and assessment of an assisted diagnosis model using machine learning for identifying adult-onset Still’s disease in fever of unknown origin: a retrospective …

Background Adult-onset Still’s disease (AOSD) is a systemic autoinflammatory disorder lacking a gold-standard diagnostic ...
BMJ Open

Implementation determinants of a planned machine learning-enabled surgical scheduling system in a high-volume orthopaedic centre in Canada: qualitative findin…

Objectives Elective non-emergent surgical wait times have increased across countries such as Canada, straining operating room ...
IEEE

A Federated Learning-Based Data Augmentation Method for Privacy Preservation Under Heterogeneous Data

Abstract: Federated learning is an important distributed machine learning paradigm. This study proposes a privacy-preserving data augmentation model for federated learning of heterogeneous data, which ...
IEEE

SCC: Synchronization Congestion Control for Multi-Tenant Learning Over Geo-Distributed Clouds

Abstract: Distributed machine learning over geo-distributed clouds enables joint training of data located in different regions, alleviating the burden of transferring large volumes of training ...