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134
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ML
2002
ACM
220views Machine Learning» more  ML 2002»
15 years 2 months ago
Bayesian Methods for Support Vector Machines: Evidence and Predictive Class Probabilities
I describe a framework for interpreting Support Vector Machines (SVMs) as maximum a posteriori (MAP) solutions to inference problems with Gaussian Process priors. This probabilisti...
Peter Sollich
120
Voted
ICIP
2003
IEEE
16 years 4 months ago
An entropy based segmentation algorithm for computer-generated document images
This paper presents an efficient compression-oriented segmentation algorithm for computer-generated document images. In this algorithm, a document image is represented in a block-...
Lijie Liu, Yan Dong, Xiaomu Song, Guoliang Fan
127
Voted
ICIP
2001
IEEE
16 years 4 months ago
Coding theoretic approach to image segmentation
This paper introduces multi-scale tree-based approaches to image segmentation, using Rissanen's coding theoretic minimum description length (MDL) principle to penalize overly...
Mário A. T. Figueiredo, Robert D. Nowak, Un...
139
Voted
ICML
2009
IEEE
16 years 3 months ago
Archipelago: nonparametric Bayesian semi-supervised learning
Semi-supervised learning (SSL), is classification where additional unlabeled data can be used to improve accuracy. Generative approaches are appealing in this situation, as a mode...
Ryan Prescott Adams, Zoubin Ghahramani
131
Voted
ICIP
2009
IEEE
15 years 14 days ago
A novel two-tier Bayesian based method for hair segmentation
In this paper, a novel two-tier Bayesian based method is proposed for hair segmentation. In the first tier, we construct a Bayesian model by integrating hair occurrence prior prob...
Dan Wang, Shiguang Shan, Wei Zeng, Hongming Zhang,...