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AAAI
2011
14 years 6 months ago
Sparse Matrix-Variate t Process Blockmodels
We consider the problem of modeling network interactions and identifying latent groups of network nodes. This problem is challenging due to the facts i) that the network nodes are...
Zenglin Xu, Feng Yan, Yuan Qi
ICIP
2002
IEEE
16 years 8 months ago
A curve evolution-based variational approach to simultaneous image restoration and segmentation
In this paper, we introduce a novel approach for simultaneous restoration and segmentation of blurred, noisy images by approaching a variant of the Mumford-Shah functional from a ...
Alan S. Willsky, Andy Tsai, Junmo Kim, Müjdat...
BIBE
2008
IEEE
137views Bioinformatics» more  BIBE 2008»
16 years 26 days ago
A sparse variational Bayesian approach for fMRI data analysis
— The aim of this work is to propose a new approach for the determination of the design matrix in fMRI experiments. The design matrix embodies all available knowledge about exper...
Vangelis P. Oikonomou, Evanthia E. Tripoliti, Dimi...
ESWS
2008
Springer
15 years 8 months ago
Two Variations on Ontology Alignment Evaluation: Methodological Issues
Evaluation of ontology alignments is in practice done in two ways: (1) assessing individual correspondences and (2) comparing the alignment to a reference alignment. However, this ...
Laura Hollink, Mark van Assem, Shenghui Wang, Anto...
NIPS
2004
15 years 7 months ago
Variational Minimax Estimation of Discrete Distributions under KL Loss
We develop a family of upper and lower bounds on the worst-case expected KL loss for estimating a discrete distribution on a finite number m of points, given N i.i.d. samples. Our...
Liam Paninski