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ICASSP
2010
IEEE
13 years 3 months ago
Variational nonparametric Bayesian Hidden Markov Model
The Hidden Markov Model (HMM) has been widely used in many applications such as speech recognition. A common challenge for applying the classical HMM is to determine the structure...
Nan Ding, Zhijian Ou
NIPS
2001
13 years 5 months ago
The Infinite Hidden Markov Model
We show that it is possible to extend hidden Markov models to have a countably infinite number of hidden states. By using the theory of Dirichlet processes we can implicitly integ...
Matthew J. Beal, Zoubin Ghahramani, Carl Edward Ra...
CRYPTO
2006
Springer
92views Cryptology» more  CRYPTO 2006»
13 years 7 months ago
Rigorous Bounds on Cryptanalytic Time/Memory Tradeoffs
In this paper we formalize a general model of cryptanalytic time/memory tradeoffs for the inversion of a random function f : {0, 1, . . . , N - 1} {0, 1, . . . , N - 1}. The model...
Elad Barkan, Eli Biham, Adi Shamir
PKDD
2009
Springer
146views Data Mining» more  PKDD 2009»
13 years 8 months ago
Parallel Subspace Sampling for Particle Filtering in Dynamic Bayesian Networks
Monitoring the variables of real world dynamic systems is a difficult task due to their inherent complexity and uncertainty. Particle Filters (PF) perform that task, yielding prob...
Eva Besada-Portas, Sergey M. Plis, Jesús Ma...
CDC
2009
IEEE
111views Control Systems» more  CDC 2009»
13 years 8 months ago
Minimal dynamical structure realisations with application to network reconstruction from data
— Network reconstruction, i.e., obtaining network structure from data, is a central theme in systems biology, economics, and engineering. Previous work introduced dynamical struc...
Ye Yuan, Guy-Bart Vincent Stan, Sean Warnick, Jorg...
ICC
2009
IEEE
123views Communications» more  ICC 2009»
13 years 10 months ago
Combining Hidden Markov Models for Improved Anomaly Detection
—In host-based intrusion detection systems (HIDS), anomaly detection involves monitoring for significant deviations from normal system behavior. Hidden Markov Models (HMMs) have...
Wael Khreich, Eric Granger, Robert Sabourin, Ali M...
ICPR
2008
IEEE
14 years 4 months ago
Approximating a non-homogeneous HMM with Dynamic Spatial Dirichlet Process
In this work we present a model that uses a Dirichlet Process (DP) with a dynamic spatial constraints to approximate a non-homogeneous hidden Markov model (NHMM). The coefficient ...
Haijun Ren, Leon N. Cooper, Liang Wu, Predrag Nesk...
CVPR
2003
IEEE
14 years 5 months ago
Switching Observation Models for Contour Tracking in Clutter
In Proc. of IEEE Conf. on CVPR'03, Madison, Wisconsin, 2003 We propose a generative model approach to contour tracking against non-stationary clutter and to coping with occlu...
Ying Wu, Gang Hua, Ting Yu