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» The Most Robust Loss Function for Boosting
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SIGIR
2011
ACM
12 years 10 months ago
A boosting approach to improving pseudo-relevance feedback
Pseudo-relevance feedback has proven effective for improving the average retrieval performance. Unfortunately, many experiments have shown that although pseudo-relevance feedback...
Yuanhua Lv, ChengXiang Zhai, Wan Chen
IDA
2002
Springer
13 years 7 months ago
Boosting strategy for classification
This paper introduces a strategy for training ensemble classifiers by analysing boosting within margin theory. We present a bound on the generalisation error of ensembled classifi...
Huma Lodhi, Grigoris J. Karakoulas, John Shawe-Tay...
DAGM
2011
Springer
12 years 7 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...
CVPR
2009
IEEE
13 years 11 months ago
Learning to associate: HybridBoosted multi-target tracker for crowded scene
We propose a learning-based hierarchical approach of multi-target tracking from a single camera by progressively associating detection responses into longer and longer track fragm...
Yuan Li, Chang Huang, Ram Nevatia
DATE
2009
IEEE
73views Hardware» more  DATE 2009»
14 years 2 months ago
A study of the Single Event Effects impact on functional mapping within Flash-based FPGAs
—Flash-based FPGAs are increasingly demanded in safety critical fields, in particular space and avionic ones, due to their non-volatile configuration memory. Although they are al...
Francesco Abate, Luca Sterpone, Massimo Violante, ...