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CIKM
2005
Springer
15 years 12 months ago
Discretization based learning approach to information retrieval
We approached the problem as learning how to order documents by estimated relevance with respect to a user query. Our support vector machines based classifier learns from the rele...
Dmitri Roussinov, Weiguo Fan, Fernando A. Das Neve...
AIIA
2009
Springer
15 years 10 months ago
Local Kernel for Brains Classification in Schizophrenia
Abstract. In this paper a novel framework for brain classification is proposed in the context of mental health research. A learning by example method is introduced by combining loc...
Umberto Castellani, E. Rossato, Vittorio Murino, M...
ICCV
2011
IEEE
14 years 6 months ago
What Characterizes a Shadow Boundary under the Sun and Sky?
Despite decades of study, robust shadow detection remains difficult, especially within a single color image. We describe a new approach to detect shadow boundaries in images of o...
Xiang Huang, Gang Hua, Jack Tumblin, Lance William...
JMLR
2012
13 years 8 months ago
Max-Margin Min-Entropy Models
We propose a new family of latent variable models called max-margin min-entropy (m3e) models, which define a distribution over the output and the hidden variables conditioned on ...
Kevin Miller, M. Pawan Kumar, Benjamin Packer, Dan...
SDM
2009
SIAM
161views Data Mining» more  SDM 2009»
16 years 3 months ago
Feature Weighted SVMs Using Receiver Operating Characteristics.
Support Vector Machines (SVMs) are a leading tool in classification and pattern recognition and the kernel function is one of its most important components. This function is used...
Shaoyi Zhang, M. Maruf Hossain, Md. Rafiul Hassan,...