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» Boosting Methods for Regression
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ANOR
2004
116views more  ANOR 2004»
13 years 9 months ago
Approximations and Randomization to Boost CSP Techniques
Abstract. In recent years we have seen an increasing interest in combining constraint satisfaction problem (CSP) formulations and linear programming (LP) based techniques for solvi...
Carla P. Gomes, David B. Shmoys
ICDM
2010
IEEE
264views Data Mining» more  ICDM 2010»
13 years 7 months ago
Block-GP: Scalable Gaussian Process Regression for Multimodal Data
Regression problems on massive data sets are ubiquitous in many application domains including the Internet, earth and space sciences, and finances. In many cases, regression algori...
Kamalika Das, Ashok N. Srivastava
ICPR
2004
IEEE
14 years 11 months ago
Real-Time Face Detection Using Boosting in Hierarchical Feature Spaces
Boosting-basedmethods have recently led to the state-ofthe-art face detection systems. In these systems, weak classifiers to be boosted are based on simple, local, Haar-like featu...
Daniel Gatica-Perez, Dong Zhang, Stan Z. Li
KDD
2009
ACM
150views Data Mining» more  KDD 2009»
14 years 10 months ago
Information theoretic regularization for semi-supervised boosting
We present novel semi-supervised boosting algorithms that incrementally build linear combinations of weak classifiers through generic functional gradient descent using both labele...
Lei Zheng, Shaojun Wang, Yan Liu, Chi-Hoon Lee
CVPR
2005
IEEE
14 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