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ICML
2008
IEEE
14 years 8 months ago
On the quantitative analysis of deep belief networks
Deep Belief Networks (DBN's) are generative models that contain many layers of hidden variables. Efficient greedy algorithms for learning and approximate inference have allow...
Ruslan Salakhutdinov, Iain Murray
ICCV
2007
IEEE
14 years 9 months ago
Fast Pixel/Part Selection with Sparse Eigenvectors
We extend the "Sparse LDA" algorithm of [7] with new sparsity bounds on 2-class separability and efficient partitioned matrix inverse techniques leading to 1000-fold spe...
Bernard Moghaddam, Yair Weiss, Shai Avidan
JMLR
2010
159views more  JMLR 2010»
13 years 2 months ago
Inference of Sparse Networks with Unobserved Variables. Application to Gene Regulatory Networks
Networks are becoming a unifying framework for modeling complex systems and network inference problems are frequently encountered in many fields. Here, I develop and apply a gener...
Nikolai Slavov
KDD
2004
ACM
132views Data Mining» more  KDD 2004»
14 years 8 months ago
Privacy preserving regression modelling via distributed computation
Reluctance of data owners to share their possibly confidential or proprietary data with others who own related databases is a serious impediment to conducting a mutually beneficia...
Ashish P. Sanil, Alan F. Karr, Xiaodong Lin, Jerom...
JMLR
2011
167views more  JMLR 2011»
13 years 2 months ago
Logistic Stick-Breaking Process
A logistic stick-breaking process (LSBP) is proposed for non-parametric clustering of general spatially- or temporally-dependent data, imposing the belief that proximate data are ...
Lu Ren, Lan Du, Lawrence Carin, David B. Dunson