A new communication-collective system, OptiReduce, speeds up AI and machine learning training across multiple cloud servers by setting time boundaries rather than waiting for every server to catch up, ...

Mohammad Adnan's 2025 Global Recognition Award honors his contributions to artificial intelligence and Amazon Web Services ...

Aditya Bhatia, Principal Software Engineer, received the 2025 Global Recognition Award for his groundbreaking work in ...

Abstract: Geo-distributed machine learning (GDML) can facilitate collaborative learning among geographically-dispersed data centers to meet the demands of distributed and privacy-preserving training ...

In contrast, short-term holders have distributed over 300,000 BTC, driven by a mix of profit-taking and capitulation. This imbalance indicates that long-term holders are accumulating more BTC than ...

Abstract: Hierarchical federated learning (HFL) is a privacy-preserving distributed machine learning framework with a client-edge-cloud hierarchy, where multiple edge servers perform partial model ...

Across five concise and engaging topics, you’ll explore the what, when, why, and how of oral assessments—learning about their benefits, practical applications, and key considerations for success.

It can be relatively cheap to gather a lot of bio-signal data. To teach a machine-learning algorithm to find a relationship between bio-signals and health outcomes, however, you need to teach the ...

Here are my personal paper reading notes (including cloud computing, resource management, systems, machine learning, deep learning, and other interesting stuffs).

It offers: A standardized interface to increase reproducibility Reduces boilerplate Automatic accumulation over batches Metrics optimized for distributed-training Automatic synchronization between ...

Experiential education has long been a part of Purdue University, shaping how students learn through hands-on experiences such as internships, service-learning and research. Yet, for much of the ...