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» A Markov chain sequence generator for power macromodeling
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BMCBI
2006
143views more  BMCBI 2006»
13 years 7 months ago
Application of protein structure alignments to iterated hidden Markov model protocols for structure prediction
Background: One of the most powerful methods for the prediction of protein structure from sequence information alone is the iterative construction of profile-type models. Because ...
Eric D. Scheeff, Philip E. Bourne
KDD
2012
ACM
254views Data Mining» more  KDD 2012»
11 years 10 months ago
Playlist prediction via metric embedding
Digital storage of personal music collections and cloud-based music services (e.g. Pandora, Spotify) have fundamentally changed how music is consumed. In particular, automatically...
Shuo Chen, Josh L. Moore, Douglas Turnbull, Thorst...
BPM
2009
Springer
175views Business» more  BPM 2009»
14 years 2 months ago
Understanding Spaghetti Models with Sequence Clustering for ProM
The goal of process mining is to discover process models from event logs. However, for processes that are not well structured and have a lot of diverse behavior, existing process m...
Gabriel M. Veiga, Diogo R. Ferreira
TSMC
2010
13 years 2 months ago
Dual Gait Generative Models for Human Motion Estimation From a Single Camera
This paper presents a general gait representation framework for video-based human motion estimation. Specifically, we want to estimate the kinematics of an unknown gait from image ...
Xin Zhang, Guoliang Fan
DAC
1997
ACM
13 years 12 months ago
Sequence Compaction for Probabilistic Analysis of Finite-State Machines
- The objective of this paper is to provide an effective technique for accurate modeling of the external input sequences that affect the behavior of Finite State Machines (FSMs). T...
Diana Marculescu, Radu Marculescu, Massoud Pedram