Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...

Review re-maps multi-view learning into four supervised scenarios and three granular sub-tiers, delivering the first unified blueprint for researchers to navigate classification, clustering, ...

One of the most difficult challenges in payment card fraud detection is extreme class imbalance. Fraudulent transactions ...

Introduction: Why Data Quality Is Harder Than Ever Data quality has always been important, but in today’s world of ...

Who is a data scientist? What does he do? What steps are involved in executing an end-to-end data science project? What roles are available in the industry? Will I need to be a good ...

Satyam Kumar’s rise from rural Bihar to elite research labs in the United States has emerged as one of the most remarkable academic journeys. Known fo.

Explore how effective governance in AI programmes hinges on engineering evidence, control, and accountability at scale for ...

Tabular foundation models are the next major unlock for AI adoption, especially in industries sitting on massive databases of ...

Enterprises face key challenges in harnessing unstructured data so they can make the most of their investments in AI, but several vendors are addressing these challenges.

The language used to describe conflicts naturally reflects assumptions about how different forms of violence emerge and develop. "For instance, we ...