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» Learning Taxonomies by Dependence Maximization
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BMCBI
2010
147views more  BMCBI 2010»
15 years 14 days ago
Learning biological network using mutual information and conditional independence
Background: Biological networks offer us a new way to investigate the interactions among different components and address the biological system as a whole. In this paper, a revers...
Dong-Chul Kim, Xiaoyu Wang, Chin-Rang Yang, Jean G...
95
Voted
ISVC
2009
Springer
15 years 7 months ago
Probabilistic Facial Feature Extraction Using Joint Distribution of Location and Texture Information
Abstract. In this work, we propose a method which can extract critical points on a face using both location and texture information. This new approach can automatically learn featu...
Mustafa Berkay Yilmaz, Hakan Erdogan, Mustafa Unel
105
Voted
CTW
2002
74views more  CTW 2002»
15 years 5 days ago
Nine Steps to Move Forward from Error
: Following celebrated failures stakeholders begin to ask questions about how to improve the systems and processes they operate, manage or depend on. In this process it is easy to ...
David D. Woods, Richard I. Cook
117
Voted
CORR
2008
Springer
98views Education» more  CORR 2008»
15 years 13 days ago
Information Acquisition and Exploitation in Multichannel Wireless Networks
A wireless system with multiple channels is considered, where each channel has several transmission states. A user learns about the instantaneous state of an available channel by ...
Sudipto Guha, Kamesh Munagala, Saswati Sarkar
BMVC
2010
14 years 10 months ago
Joint Modeling of Algorithm Behavior and Image Quality for Algorithm Performance Prediction
In this paper, we propose a framework for predicting the performance of a vision algorithm given the input image or video so as to maximize the algorithm's ability to provide...
Apurva Gala, Shishir Shah