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» Some Theory for Generalized Boosting Algorithms
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CVPR
2007
IEEE
14 years 9 months ago
Generic Face Alignment using Boosted Appearance Model
This paper proposes a discriminative framework for efficiently aligning images. Although conventional Active Appearance Models (AAM)-based approaches have achieved some success, t...
Xiaoming Liu 0002
ETVC
2008
13 years 9 months ago
Intrinsic Geometries in Learning
In a seminal paper, Amari (1998) proved that learning can be made more efficient when one uses the intrinsic Riemannian structure of the algorithms' spaces of parameters to po...
Richard Nock, Frank Nielsen
ICDM
2003
IEEE
134views Data Mining» more  ICDM 2003»
14 years 1 months ago
Cost-Sensitive Learning by Cost-Proportionate Example Weighting
We propose and evaluate a family of methods for converting classifier learning algorithms and classification theory into cost-sensitive algorithms and theory. The proposed conve...
Bianca Zadrozny, John Langford, Naoki Abe
EWSN
2004
Springer
14 years 1 months ago
Networked Slepian-Wolf: Theory and Algorithms
Abstract. In this paper, we consider the minimization of a relevant energy consumption related cost function in the context of sensor networks where correlated sources are generate...
Razvan Cristescu, Baltasar Beferull-Lozano, Martin...
CIKM
2009
Springer
14 years 2 months ago
Learning to rank from Bayesian decision inference
Ranking is a key problem in many information retrieval (IR) applications, such as document retrieval and collaborative filtering. In this paper, we address the issue of learning ...
Jen-Wei Kuo, Pu-Jen Cheng, Hsin-Min Wang