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ECAI
2004
Springer
15 years 7 months ago
Learning Complex and Sparse Events in Long Sequences
The Hierarchical Hidden Markov Model (HHMM) is a well formalized tool suitable to model complex patterns in long temporal or spatial sequences. Even if effective algorithms are ava...
Marco Botta, Ugo Galassi, Attilio Giordana
ATAL
2008
Springer
15 years 3 months ago
The permutable POMDP: fast solutions to POMDPs for preference elicitation
The ability for an agent to reason under uncertainty is crucial for many planning applications, since an agent rarely has access to complete, error-free information about its envi...
Finale Doshi, Nicholas Roy
IJFCS
2008
49views more  IJFCS 2008»
15 years 1 months ago
A Markovian Approach for the Analysis of the gene Structure
Hidden Markov models (HMMs) are effective tools to detect series of statistically homogeneous structures, but they are not well suited to analyse complex structures. Numerous meth...
Christelle Melo de Lima, Laurent Gueguen, Christia...
TASLP
2002
96views more  TASLP 2002»
15 years 1 months ago
MAP speaker adaptation of state duration distributions for speech recognition
This paper presents a framework for maximum a posteriori (MAP) speaker adaptation of state duration distributions in hidden Markov models (HMM). Four key issues of MAP estimation, ...
Néstor Becerra Yoma, Jorge Silva Sán...
CORR
2010
Springer
122views Education» more  CORR 2010»
14 years 8 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