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» Learning nonsingular phylogenies and hidden Markov models
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ICASSP
2009
IEEE
14 years 3 months ago
A variational EM algorithm for learning eigenvoice parameters in mixed signals
We derive an efficient learning algorithm for model-based source separation for use on single channel speech mixtures where the precise source characteristics are not known a pri...
Ron J. Weiss, Daniel P. W. Ellis
ICASSP
2010
IEEE
13 years 8 months ago
Automatic state discovery for unstructured audio scene classification
In this paper we present a novel scheme for unstructured audio scene classification that possesses three highly desirable and powerful features: autonomy, scalability, and robust...
Julian Ramos, Sajid M. Siddiqi, Artur Dubrawski, G...
CVPR
1999
IEEE
14 years 10 months ago
Time-Series Classification Using Mixed-State Dynamic Bayesian Networks
We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
Vladimir Pavlovic, Brendan J. Frey, Thomas S. Huan...
FLAIRS
2004
13 years 10 months ago
Semi-Supervised Sequence Classification with HMMs
Using unlabeled data to help supervised learning has become an increasingly attractive methodology and proven to be effective in many applications. This paper applies semi-supervi...
Shi Zhong
EDM
2008
169views Data Mining» more  EDM 2008»
13 years 10 months ago
Mining Student Behavior Models in Learning-by-Teaching Environments
This paper discusses our approach to building models and analyzing student behaviors in different versions of our learning by teaching environment where students learn by teaching ...
Hogyeong Jeong, Gautam Biswas