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109
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ECIR
2011
Springer
14 years 5 months ago
Weight-Based Boosting Model for Cross-Domain Relevance Ranking Adaptation
Adaptation techniques based on importance weighting were shown effective for RankSVM and RankNet, viz., each training instance is assigned a target weight denoting its importance ...
Peng Cai, Wei Gao, Kam-Fai Wong, Aoying Zhou
199
Voted
CVPR
2009
IEEE
16 years 9 months ago
Regularized Multi-Class Semi-Supervised Boosting
Many semi-supervised learning algorithms only deal with binary classification. Their extension to the multi-class problem is usually obtained by repeatedly solving a set of bina...
Amir Saffari, Christian Leistner, Horst Bischof
124
Voted
CVPR
2005
IEEE
16 years 4 months ago
Fast Spatial Pattern Discovery Integrating Boosting with Constellations of Contextual Descriptors
We present a novel approach for fast object class recognition incorporating contextual information into boosting. The object is represented as a constellation of generalized corre...
Jaume Amores, Nicu Sebe, Petia Radeva
119
Voted
CVPR
2008
IEEE
16 years 4 months ago
Boosting ordinal features for accurate and fast iris recognition
In this paper, we present a novel iris recognition method based on learned ordinal features.Firstly, taking full advantages of the properties of iris textures, a new iris represen...
Zhaofeng He, Zhenan Sun, Tieniu Tan, Xianchao Qiu,...
99
Voted
ICML
2008
IEEE
16 years 3 months ago
Boosting with incomplete information
In real-world machine learning problems, it is very common that part of the input feature vector is incomplete: either not available, missing, or corrupted. In this paper, we pres...
Feng Jiao, Gholamreza Haffari, Greg Mori, Shaojun ...