Data processing: artificial intelligence – Machine learning
Reexamination Certificate
2006-03-21
2006-03-21
Hirl, Joseph P. (Department: 2129)
Data processing: artificial intelligence
Machine learning
C706S025000, C706S047000, C706S048000
Reexamination Certificate
active
07016881
ABSTRACT:
A novel statistical learning procedure that can be applied to many machine-learning applications is presented. Although this boosting learning procedure is described with respect to its applicability to face detection, it can be applied to speech recognition, text classification, image retrieval, document routing, online learning and medical diagnosis classification problems.
REFERENCES:
Robert E. Schapire et al, Improved Boosting Algorithms Using Confidence-Rated Predictions, 1998, Machine Learning, In Proceedings of the Eleventh Annual Conference on Computational Learning Theory, p 80-91.
P. Pudil et al., Floating Search Methods for Feature Selection With Nonmonotonic Criteria Functions, Department of Electronic and Electrical Engineering, University of Surrey Guildford, UK, 1994.
Li ZiQing
Zhang ZhenQiu
Zhu Long
Lyon Katrina A.
Lyon & Harr LLP
Microsoft Corp.
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