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» Image Based Regression Using Boosting Method
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CVPR
2005
IEEE
15 years 3 months ago
Jensen-Shannon Boosting Learning for Object Recognition
In this paper, we propose a novel learning method, called Jensen-Shannon Boosting (JSBoost) and demonstrate its application to object recognition. JSBoost incorporates Jensen-Shan...
Xiangsheng Huang, Stan Z. Li, Yangsheng Wang
PREMI
2011
Springer
14 years 17 days ago
Feature Set Selection for On-Line Signatures Using Selection of Regression Variables
Abstract. In this paper we approach feature set selection phase in signature verification by applying the method for selection of regression variables based on Mallows Cp criterio...
Desislava Boyadzieva, Georgi Gluhchev
CORR
2012
Springer
232views Education» more  CORR 2012»
13 years 5 months ago
Smoothing Proximal Gradient Method for General Structured Sparse Learning
We study the problem of learning high dimensional regression models regularized by a structured-sparsity-inducing penalty that encodes prior structural information on either input...
Xi Chen, Qihang Lin, Seyoung Kim, Jaime G. Carbone...
ICIP
2010
IEEE
14 years 7 months ago
Generalized YUV interpolation of CFA images
This paper presents a simple yet effective color filter array (CFA) interpolation algorithm. It is based on a linear interpolating kernel, but operates on YUV space, which results...
Meng Wang, Thierry Blu
ICDM
2009
IEEE
172views Data Mining» more  ICDM 2009»
15 years 4 months ago
Sparse Least-Squares Methods in the Parallel Machine Learning (PML) Framework
—We describe parallel methods for solving large-scale, high-dimensional, sparse least-squares problems that arise in machine learning applications such as document classificatio...
Ramesh Natarajan, Vikas Sindhwani, Shirish Tatikon...