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» Mixed state estimation for a linear Gaussian Markov model
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JMLR
2011
148views more  JMLR 2011»
13 years 2 months ago
Bayesian Generalized Kernel Mixed Models
We propose a fully Bayesian methodology for generalized kernel mixed models (GKMMs), which are extensions of generalized linear mixed models in the feature space induced by a repr...
Zhihua Zhang, Guang Dai, Michael I. Jordan
NIPS
2001
13 years 8 months ago
Predictive Representations of State
We show that states of a dynamical system can be usefully represented by multi-step, action-conditional predictions of future observations. State representations that are grounded...
Michael L. Littman, Richard S. Sutton, Satinder P....
CORR
2010
Springer
122views Education» more  CORR 2010»
13 years 2 months ago
Concavity of Mutual Information Rate for Input-Restricted Finite-State Memoryless Channels at High SNR
We consider a finite-state memoryless channel with i.i.d. channel state and the input Markov process supported on a mixing finite-type constraint. We discuss the asymptotic behavio...
Guangyue Han, Brian H. Marcus
IWCMC
2006
ACM
14 years 1 months ago
System approach to intrusion detection using hidden Markov model
In an era of cooperating ad hoc networks and pervasive wireless connectivity, we are becoming more vulnerable to malicious attacks. Many of these attacks are silent in nature and ...
Rahul Khanna, Huaping Liu
AVSS
2007
IEEE
14 years 1 months ago
Vehicular traffic density estimation via statistical methods with automated state learning
This paper proposes a novel approach of combining an unsupervised clustering scheme called AutoClass with Hidden Markov Models (HMMs) to determine the traffic density state in a R...
Evan Tan, Jing Chen