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CIKM
2005
Springer
14 years 11 months ago
Using RankBoost to compare retrieval systems
This paper presents a new pooling method for constructing the assessment sets used in the evaluation of retrieval systems. Our proposal is based on RankBoost, a machine learning v...
Huyen-Trang Vu, Patrick Gallinari
78
Voted
WWW
2005
ACM
15 years 10 months ago
Boosting SVM classifiers by ensemble
By far, the support vector machines (SVM) achieve the state-of-theart performance for the text classification (TC) tasks. Due to the complexity of the TC problems, it becomes a ch...
Yan-Shi Dong, Ke-Song Han
CVPR
2005
IEEE
15 years 11 months ago
Robust Boosting for Learning from Few Examples
We present and analyze a novel regularization technique based on enhancing our dataset with corrupted copies of our original data. The motivation is that since the learning algori...
Lior Wolf, Ian Martin
DAGM
2011
Springer
13 years 9 months ago
Multiple Instance Boosting for Face Recognition in Videos
For face recognition from video streams often cues such as transcripts, subtitles or on-screen text are available. This information could be very valuable for improving the recogni...
Paul Wohlhart, Martin Köstinger, Peter M. Rot...
112
Voted
ACCV
2007
Springer
15 years 1 months ago
A Cascade of Feed-Forward Classifiers for Fast Pedestrian Detection
We develop a method that can detect humans in a single image based on a new cascaded structure. In our approach, both the rectangle features and 1-D edge-orientation features are e...
Yu-Ting Chen, Chu-Song Chen