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» Approximate Probabilistic Model Checking
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AAAI
2000
15 years 1 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»
14 years 11 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»
14 years 11 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
16 years 23 days 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»
14 years 11 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