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» Using Problems to Learn Service-Oriented Computing
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CVPR
2007
IEEE
15 years 8 months ago
Diverse Active Ranking for Multimedia Search
Interactively learning from a small sample of unlabeled examples is an enormously challenging task, one that often arises in vision applications. Relevance feedback and more recen...
ShyamSundar Rajaram, Charlie K. Dagli, Nemanja Pet...
ICML
2008
IEEE
16 years 5 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 ...
ECCV
2006
Springer
16 years 6 months ago
Tracking Objects Across Cameras by Incrementally Learning Inter-camera Colour Calibration and Patterns of Activity
This paper presents a scalable solution to the problem of tracking objects across spatially separated, uncalibrated, non-overlapping cameras. Unlike other approaches this technique...
Andrew Gilbert, Richard Bowden
ICPR
2008
IEEE
15 years 11 months ago
Utilizing non-uniform cost learning for active control of inter-class confusion
In this paper, we demonstrate the use of learning with non-uniform error-cost as a novel technique to design a multiclass cost-sensitive classifier. We investigate two important ...
Dwi Sianto Mansjur, Qiang Fu, Biing-Hwang Juang
EMNLP
2009
15 years 2 months ago
Multi-Class Confidence Weighted Algorithms
The recently introduced online confidence-weighted (CW) learning algorithm for binary classification performs well on many binary NLP tasks. However, for multi-class problems CW l...
Koby Crammer, Mark Dredze, Alex Kulesza