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ICDM
2008
IEEE
230views Data Mining» more  ICDM 2008»
14 years 4 months ago
Evolutionary Clustering by Hierarchical Dirichlet Process with Hidden Markov State
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, ...
VALUETOOLS
2006
ACM
125views Hardware» more  VALUETOOLS 2006»
14 years 4 months ago
An approximative method for calculating performance measures of Markov processes
We present a new approximation method called value extrapolation for Markov processes with large or infinite state spaces. The method can be applied for calculating any performan...
Juha Leino, Jorma T. Virtamo
ICANN
2009
Springer
14 years 2 months ago
Switching Hidden Markov Models for Learning of Motion Patterns in Videos
Abstract. Building on the current understanding of neural architecture of the visual cortex, we present a graphical model for learning and classification of motion patterns in vid...
Matthias Höffken, Daniel Oberhoff, Marina Kol...
ECML
2006
Springer
14 years 1 months ago
Deconvolutive Clustering of Markov States
In this paper we formulate the problem of grouping the states of a discrete Markov chain of arbitrary order simultaneously with deconvolving its transition probabilities. As the na...
Ata Kabán, Xin Wang
CORR
2010
Springer
147views Education» more  CORR 2010»
13 years 10 months ago
High-Rate Quantization for the Neyman-Pearson Detection of Hidden Markov Processes
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...