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NIPS
2007
13 years 7 months ago
A General Boosting Method and its Application to Learning Ranking Functions for Web Search
We present a general boosting method extending functional gradient boosting to optimize complex loss functions that are encountered in many machine learning problems. Our approach...
Zhaohui Zheng, Hongyuan Zha, Tong Zhang, Olivier C...
CVPR
2006
IEEE
14 years 8 months ago
AdaBoost.MRF: Boosted Markov Random Forests and Application to Multilevel Activity Recognition
Activity recognition is an important issue in building intelligent monitoring systems. We address the recognition of multilevel activities in this paper via a conditional Markov r...
Tran The Truyen, Dinh Q. Phung, Svetha Venkatesh, ...
CVPR
2006
IEEE
14 years 8 months ago
Probabilistic 3D Polyp Detection in CT Images: The Role of Sample Alignment
Automatic polyp detection is an increasingly important task in medical imaging with virtual colonoscopy [15] being widely used. In this paper, we present a 3D object detection alg...
Zhuowen Tu, Xiang Sean Zhou, Luca Bogoni, Adrian B...
KDD
2008
ACM
120views Data Mining» more  KDD 2008»
14 years 6 months ago
Multi-class cost-sensitive boosting with p-norm loss functions
We propose a family of novel cost-sensitive boosting methods for multi-class classification by applying the theory of gradient boosting to p-norm based cost functionals. We establ...
Aurelie C. Lozano, Naoki Abe
ECAI
2006
Springer
13 years 10 months ago
A Real Generalization of Discrete AdaBoost
Scaling discrete AdaBoost to handle real-valued weak hypotheses has often been done under the auspices of convex optimization, but little is generally known from the original boost...
Richard Nock, Frank Nielsen