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SDM
2004
SIAM
142views Data Mining» more  SDM 2004»
13 years 11 months ago
Learning to Read Between the Lines: The Aspect Bernoulli Model
We present a novel probabilistic multiple cause model for binary observations. In contrast to other approaches, the model is linear and it infers reasons behind both observed and ...
Ata Kabán, Ella Bingham, T. Hirsimäki
SDM
2004
SIAM
218views Data Mining» more  SDM 2004»
13 years 11 months ago
Mixture Density Mercer Kernels: A Method to Learn Kernels Directly from Data
This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture density e...
Ashok N. Srivastava
CORR
2010
Springer
193views Education» more  CORR 2010»
13 years 8 months ago
A Probabilistic Approach for Learning Folksonomies from Structured Data
Learning structured representations has emerged as an important problem in many domains, including document and Web data mining, bioinformatics, and image analysis. One approach t...
Anon Plangprasopchok, Kristina Lerman, Lise Getoor
RSFDGRC
2005
Springer
208views Data Mining» more  RSFDGRC 2005»
14 years 3 months ago
On the Complexity of Probabilistic Inference in Singly Connected Bayesian Networks
Abstract. In this paper, we revisit the consensus of computational complexity on exact inference in Bayesian networks. We point out that even in singly connected Bayesian networks,...
Dan Wu, Cory J. Butz
ANLP
2000
163views more  ANLP 2000»
13 years 11 months ago
Automatic construction of parallel English-Chinese corpus for cross-language information retrieval
A major obstacle to the construction of a probabilistic translation model is the lack of large parallel corpora. In this paper we first describe a parallel text mining system that...
Jiang Chen, Jian-Yun Nie