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IJON
2010
109views more  IJON 2010»
15 years 29 days ago
Variational inference for Student-t MLP models
This paper presents a novel methodology to infer parameters of probabilistic models whose output noise is a Student-t distribution. The method is an extension of earlier work for ...
Hang T. Nguyen, Ian T. Nabney
191
Voted
JMLR
2010
150views more  JMLR 2010»
15 years 28 days ago
Supervised Dimension Reduction Using Bayesian Mixture Modeling
We develop a Bayesian framework for supervised dimension reduction using a flexible nonparametric Bayesian mixture modeling approach. Our method retrieves the dimension reduction ...
Kai Mao, Feng Liang, Sayan Mukherjee
CVPR
2005
IEEE
16 years 8 months ago
A Dynamic Conditional Random Field Model for Object Segmentation in Image Sequences
This paper presents a dynamic conditional random field (DCRF) model to integrate contextual constraints for object segmentation in image sequences. Spatial and temporal dependenci...
Qiang Ji, Yang Wang 0002
ICASSP
2008
IEEE
16 years 18 days ago
Modeling regulatory sites with higher order position-dependent weight matrices
Identification of regulatory signals in DNA depends on the nature and quality of the patterns of representative sequences. These patterns are constructed from training sets of se...
Hossein Zare, Mostafa Kaveh, Arkady B. Khodursky
ICASSP
2008
IEEE
16 years 18 days ago
Bayesian extensions to non-negative matrix factorisation for audio signal modelling
We describe the underlying probabilistic generative signal model of non-negative matrix factorisation (NMF) and propose a realistic conjugate priors on the matrices to be estimate...
Tuomas Virtanen, Ali Taylan Cemgil, Simon J. Godsi...