Somdip is the Chief Scientist of Nosh Technologies, an MIT Innovator Under 35 and a Professor of Practice (AI/ML) at the Woxsen University. As a leader in the artificial intelligence (AI) domain and a ...

The review reports that blockchain-enhanced federated learning systems typically achieve slightly lower raw accuracy than ...

One of the key challenges of machine learning is the need for large amounts of data. Gathering training datasets for machine learning models poses privacy, security, and processing risks that ...

Editor’s note: This post from Duke’s Fuqua School of Business is the second article about the future of machine learning in WRAL TechWire’s regular “Deep Dive” feature. Earlier this month Deep Dive ...

In this special guest feature, Gary M. Shiffman, PhD, Co-founder and CEO, Consilient, takes a look at Federated Machine Learning, the branch of machine learning that’s sure to be a revolution for FCC ...

With the introduction of Google's Tensor Flow federated, the hype around federated machine learning is surging. But there are important questions about data privacy, performance and cost that need ...

As machine learning becomes more pervasive in the data center and the cloud there will be a need to share and aggregate information and knowledge but without exposing or moving the underlying data.

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Vivek Yadav, an engineering manager from ...

Machine Learning has revolutionized various industries by enabling intelligent systems to learn from data and make accurate predictions or decisions. However, traditional centralized machine learning ...

As data privacy collides with AI’s rapid expansion, the Berkeley-trained technologist explains how a new generation of models ...