The decentralized quickest change detection problem is studied in sensor networks, where a set of sensors receive observations from a hidden Markov model (HMM) X and send sensor messages to a central processor, called the fusion center, which makes a final decision when observations are stopped. It is assumed that the parameter θ in the hidden Markov model for X changes from θ0 to θ1 at some un...

There exist many storage formats for the in-memory representation of sparse matrices. Choosing the format that yields the quickest processing of any given sparse matrix requires considering the exact non-zero structure of the matrix, as well as the current execution environment. Each of these factors can change at runtime. The matrix structure can vary as computation progresses, while the envir...

Agile localization of anomalous events plays a pivotal role in enhancing the overall reliability of the grid and avoiding cascading failures. This is especially of paramount significance in the large-scale grids due to their geographical expansions and the large volume of data generated. This paper proposes a stochastic graphical framework, by leveraging which it aims to localize the anomalies ...

Consider $n$ random variables forming a Markov field (MRF). The true model of the MRF is unknown, and it assumed to belong binary set. objective sequentially sample (one-at-a-time) such that can be detected with fewest number samples,...