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» Inference for Multiplicative Models
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NIPS
2003
15 years 5 months ago
Pairwise Clustering and Graphical Models
Significant progress in clustering has been achieved by algorithms that are based on pairwise affinities between the datapoints. In particular, spectral clustering methods have ...
Noam Shental, Assaf Zomet, Tomer Hertz, Yair Weiss
WS
2008
ACM
15 years 4 months ago
Translating the Foundational Model of Anatomy into OWL
The Foundational Model of Anatomy (FMA) [7] represents the result of manual and disciplined modeling of the structural organization of the human body. Many workers in medical info...
Natalya Fridman Noy, Daniel L. Rubin
JMLR
2010
202views more  JMLR 2010»
14 years 11 months ago
Learning the Structure of Deep Sparse Graphical Models
Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
Ryan Prescott Adams, Hanna M. Wallach, Zoubin Ghah...
JMLR
2012
13 years 6 months ago
Learning Low-order Models for Enforcing High-order Statistics
Models such as pairwise conditional random fields (CRFs) are extremely popular in computer vision and various other machine learning disciplines. However, they have limited expre...
Patrick Pletscher, Pushmeet Kohli
ECML
2006
Springer
15 years 8 months ago
Variational Bayesian Dirichlet-Multinomial Allocation for Exponential Family Mixtures
Abstract. This paper studies a Bayesian framework for density modeling with mixture of exponential family distributions. Variational Bayesian Dirichlet-Multinomial allocation (VBDM...
Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Krieg...