Researchers report that the integration of machine learning and Internet of Things (IoT) technologies is enabling a new generation of intelligent industrial environments capable of real-time ...

When a worker thread completes a task, it doesn't return a sprawling transcript of every failed attempt; it returns a ...

Practical Application: The authors propose QFI-Informed Mutation (QIm), a heuristic that adapts mutation probabilities using diagonal QFI entries. QIm outperforms uniform and random-restart baselines, ...

Abstract: This work studies fundamental limits for recovering the underlying correspondence among multiple correlated random graphs. We identify a necessary condition for any algorithm to correctly ...

ABSTRACT: A new nano-based architectural design of multiple-stream convolutional homeomorphic error-control coding will be conducted, and a corresponding hierarchical implementation of important class ...

Abstract: Random walk centrality is a fundamental metric in graph mining for quantifying node importance and influence, defined as the weighted average of hitting times to a node from all other nodes.

In this video, we explore why Spotify's shuffle feature isn't truly random and operates based on an algorithm. We discuss the reasons behind our preferences for non-random shuffle, the results of an ...

This contribution is part of the special series of Inaugural Articles by members of the National Academy of Sciences elected in 2024. Many real-world networks change dynamically but can be notoriously ...

ABSTRACT: Missing data remains a persistent and pervasive challenge across a wide range of domains, significantly impacting data analysis pipelines, predictive modeling outcomes, and the reliability ...