This paper investigates the decentralized detection of Hidden Markov Processes using the NeymanPearson test. We consider a network formed by a large number of distributed sensors....
Joffrey Villard, Pascal Bianchi, Eric Moulines, Pa...
We study the entropy rate of a hidden Markov process (HMP) defined by observing the output of a binary symmetric channel whose input is a first-order binary Markov process. Despit...
Philippe Jacquet, Gadiel Seroussi, Wojciech Szpank...
We introduce a new probability distribution over a potentially infinite number of binary Markov chains which we call the Markov Indian buffet process. This process extends the IBP...
We are dealing in this paper with audio segmentation. We propose a two level segmentation process that enables the audio tracks to be sampled in short sequences which are classifi...
This paper studies evolutionary clustering, which is a recently hot topic with many important applications, noticeably in social network analysis. In this paper, based on the rece...
Tianbing Xu, Zhongfei (Mark) Zhang, Philip S. Yu, ...