IEEE

Temporal Threat Recognition in Supply Chains: Integrating Hidden Markov Models for Proactive Security with AI-Driven Automated Threat Hunting

Abstract: In order to tackle the pressing problem of “Temporal Threat Recognition in Supply Chains,” this study presents a novel integrated model that combines RNNs with Hidden Markov Models (HMMs).

Nearly invisible galaxy may be built mostly of dark matter, Hubble finds

A tight clump of four star clusters sits in the Perseus galaxy cluster, and at first glance it looks like nothing special. No ...

Options Corner: Palantir Stock's Brutal Start Is Finally Showing Signs Of Improvement

While Palantir has technically started the new year deep in red ink, the smart money's relaxed hedging may signal optimism ...
IEEE

Adaptive Social Learning for Slow Markov Chains

Abstract: This paper studies the problem of interconnected agents collaborating to track a dynamic state from partially informative observations, where the state follows a slow finite-state Markov ...