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» A New Discriminative Kernel From Probabilistic Models
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KDD
2006
ACM
147views Data Mining» more  KDD 2006»
15 years 10 months ago
Summarizing itemset patterns using probabilistic models
In this paper, we propose a novel probabilistic approach to summarize frequent itemset patterns. Such techniques are useful for summarization, post-processing, and end-user interp...
Chao Wang, Srinivasan Parthasarathy
ICASSP
2011
IEEE
14 years 1 months ago
Discriminative Training for direct minimization of deletion, insertion and substitution errors
In this paper, we follow the minimum error principle for acoustic modeling and formulate error objectives in insertion, deletion, and substitution separately for minimization duri...
Sunghwan Shin, Ho-Young Jung, Biing-Hwang Juang
ISVC
2009
Springer
15 years 4 months ago
Probabilistic Facial Feature Extraction Using Joint Distribution of Location and Texture Information
Abstract. In this work, we propose a method which can extract critical points on a face using both location and texture information. This new approach can automatically learn featu...
Mustafa Berkay Yilmaz, Hakan Erdogan, Mustafa Unel
ICML
2004
IEEE
15 years 10 months ago
Approximate inference by Markov chains on union spaces
A standard method for approximating averages in probabilistic models is to construct a Markov chain in the product space of the random variables with the desired equilibrium distr...
Max Welling, Michal Rosen-Zvi, Yee Whye Teh
ICDCS
2010
IEEE
14 years 11 months ago
Link-Centric Probabilistic Coverage Model for Transceiver-Free Object Detection in Wireless Networks
Abstract--Sensing coverage is essential for most applications in wireless networks. In traditional coverage problem study, the disk coverage model has been widely applied because o...
Dian Zhang, Yunhuai Liu, Lionel M. Ni