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» Approximate Probabilistic Model Checking
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AAAI
2000
13 years 9 months ago
Multivariate Clustering by Dynamics
We present a Bayesian clustering algorithm for multivariate time series. A clustering is regarded as a probabilistic model in which the unknown auto-correlation structure of a tim...
Marco Ramoni, Paola Sebastiani, Paul R. Cohen
TNN
1998
89views more  TNN 1998»
13 years 7 months ago
Fast training of recurrent networks based on the EM algorithm
— In this work, a probabilistic model is established for recurrent networks. The EM (expectation-maximization) algorithm is then applied to derive a new fast training algorithm f...
Sheng Ma, Chuanyi Ji
TIT
2002
62views more  TIT 2002»
13 years 7 months ago
Maximum-likelihood binary shift-register synthesis from noisy observations
We consider the problem of estimating the feedback coefficients of a linear feedback shift register (LFSR) based on noisy observations. In the current approach, the coefficients a...
Todd K. Moon
DAC
2000
ACM
14 years 8 months ago
To split or to conjoin: the question in image computation
Image computation is the key step in fixpoint computations that are extensively used in model checking. Two techniques have been used for this step: one based on conjunction of the...
In-Ho Moon, James H. Kukula, Kavita Ravi, Fabio So...
JMLR
2006
138views more  JMLR 2006»
13 years 7 months ago
Noisy-OR Component Analysis and its Application to Link Analysis
We develop a new component analysis framework, the Noisy-Or Component Analyzer (NOCA), that targets high-dimensional binary data. NOCA is a probabilistic latent variable model tha...
Tomás Singliar, Milos Hauskrecht