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ICIP
2002
IEEE
16 years 9 months ago
Boosting face recognition on a large-scale database
Performance of many state-of-the-art face recognition (FR) methods deteriorates rapidly, when large in size databases are considered. In this paper, we propose a novel clustering ...
Juwei Lu, Konstantinos N. Plataniotis
166
Voted
ICML
2008
IEEE
16 years 8 months ago
ManifoldBoost: stagewise function approximation for fully-, semi- and un-supervised learning
We introduce a boosting framework to solve a classification problem with added manifold and ambient regularization costs. It allows for a natural extension of boosting into both s...
Nicolas Loeff, David A. Forsyth, Deepak Ramachandr...
PLDI
2005
ACM
16 years 1 months ago
Formal loop merging for signal transforms
A critical optimization in the domain of linear signal transforms, such as the discrete Fourier transform (DFT), is loop merging, which increases data locality and reuse and thus ...
Franz Franchetti, Yevgen Voronenko, Markus Pü...
239
Voted
NIPS
2001
15 years 8 months ago
Algorithmic Luckiness
Classical statistical learning theory studies the generalisation performance of machine learning algorithms rather indirectly. One of the main detours is that algorithms are studi...
Ralf Herbrich, Robert C. Williamson
161
Voted
ECCV
2004
Springer
16 years 9 months ago
Dynamic Visual Search Using Inner-Scene Similarity: Algorithms and Inherent Limitations
Abstract. A dynamic visual search framework based mainly on innerscene similarity is proposed. Algorithms as well as measures quantifying the difficulty of search tasks are suggest...
Tamar Avraham, Michael Lindenbaum