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» The Most Robust Loss Function for Boosting
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SIGIR
2011
ACM
14 years 11 days 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
14 years 9 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
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...
CVPR
2009
IEEE
15 years 1 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»
15 years 4 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, ...