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JMLR
2010
129views more  JMLR 2010»
10 years 8 months ago
Expectation Truncation and the Benefits of Preselection In Training Generative Models
We show how a preselection of hidden variables can be used to efficiently train generative models with binary hidden variables. The approach is based on Expectation Maximization (...
Jörg Lücke, Julian Eggert
TNN
2008
90views more  TNN 2008»
11 years 1 months ago
Distributed EM Algorithm for Gaussian Mixtures in Sensor Networks
Abstract--This paper presents a distributed expectation
Dongbing Gu
DMIN
2006
125views Data Mining» more  DMIN 2006»
11 years 2 months ago
Privacy-Preserving Bayesian Network Learning From Heterogeneous Distributed Data
In this paper, we propose a post randomization technique to learn a Bayesian network (BN) from distributed heterogeneous data, in a privacy sensitive fashion. In this case, two or ...
Jianjie Ma, Krishnamoorthy Sivakumar
KDD
1998
ACM
99views Data Mining» more  KDD 1998»
11 years 5 months ago
On the Efficient Gathering of Sufficient Statistics for Classification from Large SQL Databases
For a wide variety of classification algorithms, scalability to large databases can be achieved by observing that most algorithms are driven by a set of sufficient statistics that...
Goetz Graefe, Usama M. Fayyad, Surajit Chaudhuri
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