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ICPR
2010
IEEE
14 years 1 months ago
Localized Multiple Kernel Regression
Multiple kernel learning (MKL) uses a weighted combination of kernels where the weight of each kernel is optimized during training. However, MKL assigns the same weight to a kerne...
Mehmet Gönen, Ethem Alpaydin
ICPR
2010
IEEE
14 years 1 months ago
Unsupervised Evaluation Methods Based on Local Gray-Intensity Variances for Binarization of Historical Documents
Abstract--We attempt to evaluate the efficacy of six unsupervised evaluation method to tune Sauvola's threshold in optical character recognition (OCR) applications. We propose...
Marte Alejandro Ramírez-Ortegón, Raul Rojas
AROBOTS
2008
104views more  AROBOTS 2008»
13 years 10 months ago
Modeling dynamic scenarios for local sensor-based motion planning
This paper addresses the modeling of the static and dynamic parts of the scenario and how to use this information with a sensor-based motion planning system. The contribution in th...
Luis Montesano, Javier Minguez, Luis Montano
JAIR
2006
92views more  JAIR 2006»
13 years 10 months ago
Dynamic Local Search for the Maximum Clique Problem
In this paper, we introduce DLS-MC, a new stochastic local search algorithm for the maximum clique problem. DLS-MC alternates between phases of iterative improvement, during which...
Wayne J. Pullan, Holger H. Hoos
NIPS
1994
13 years 11 months ago
Active Learning with Statistical Models
For many types of machine learning algorithms, one can compute the statistically optimal" way to select training data. In this paper, we review how optimal data selection tec...
David A. Cohn, Zoubin Ghahramani, Michael I. Jorda...