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CVPR
2006
IEEE
14 years 9 months ago
Shape-Based Approach to Robust Image Segmentation using Kernel PCA
Segmentation involves separating an object from the background. In this work, we propose a novel segmentation method combining image information with prior shape knowledge, within...
Samuel Dambreville, Yogesh Rathi, Allen Tannenbaum
ICCV
2009
IEEE
1184views Computer Vision» more  ICCV 2009»
15 years 18 days ago
Learning Based Digital Matting
We cast some new insights into solving the digital matting problem by treating it as a semi-supervised learning task in machine learning. A local learning based approach and a g...
Yuanjie Zheng, Chandra Kambhamettu
ACL
2012
11 years 10 months ago
Improving Word Representations via Global Context and Multiple Word Prototypes
Unsupervised word representations are very useful in NLP tasks both as inputs to learning algorithms and as extra word features in NLP systems. However, most of these models are b...
Eric H. Huang, Richard Socher, Christopher D. Mann...
ICML
2009
IEEE
14 years 8 months ago
A majorization-minimization algorithm for (multiple) hyperparameter learning
We present a general Bayesian framework for hyperparameter tuning in L2-regularized supervised learning models. Paradoxically, our algorithm works by first analytically integratin...
Chuan-Sheng Foo, Chuong B. Do, Andrew Y. Ng
ECAI
2010
Springer
13 years 5 months ago
Feature Selection by Approximating the Markov Blanket in a Kernel-Induced Space
The proposed feature selection method aims to find a minimum subset of the most informative variables for classification/regression by efficiently approximating the Markov Blanket ...
Qiang Lou, Zoran Obradovic