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» Maximum entropy methods for biological sequence modeling
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ICASSP
2008
IEEE
14 years 3 months ago
Modeling the intonation of discourse segments for improved online dialog ACT tagging
Prosody is an important cue for identifying dialog acts. In this paper, we show that modeling the sequence of acousticprosodic values as n-gram features with a maximum entropy mod...
Vivek Kumar Rangarajan Sridhar, Shrikanth Narayana...
CIBCB
2007
IEEE
14 years 1 months ago
Prediction of Enzyme Catalytic Sites from Sequence Using Neural Networks
The accurate prediction of enzyme catalytic sites remains an open problem in bioinformatics. Recently, several structure-based methods have become popular; however, few robust seq...
Swati Pande, Amar Raheja, Dennis R. Livesay
ICIP
1998
IEEE
14 years 10 months ago
Reducing the Computational Complexity of a Map Post-Processing Algorithm for Video Sequences
Maximum a posteriori (MAP) filtering using the HuberMarkov random field (HMRF) image model has been shown in the past to be an effective method of reducing compression artifacts i...
Mark A. Robertson, Robert L. Stevenson
ECAI
2004
Springer
14 years 2 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
INFOCOM
2006
IEEE
14 years 3 months ago
A Quasi-Species Approach for Modeling the Dynamics of Polymorphic Worms
— Polymorphic worms can change their byte sequence as they replicate and propagate, thwarting the traditional signature analysis techniques used by many intrusion detection syste...
Bradley Stephenson, Biplab Sikdar