Sciweavers

BMVC
2010
13 years 1 months ago
Accounting for the Relative Importance of Objects in Image Retrieval
We introduce a method for image retrieval that leverages the implicit information about object importance conveyed by the list of keyword tags a person supplies for an image. We p...
Sung Ju Hwang, Kristen Grauman
JCB
2008
82views more  JCB 2008»
13 years 2 months ago
Determining Nucleolar Association from Sequence by Leveraging Protein-Protein Interactions
Controlled intra-nuclear organisation of proteins is critical for sustaining correct function of the cell. Proteins and RNA are transported by passive diffusion and associate with...
Mikael Bodén, Rohan D. Teasdale
JIIS
2006
73views more  JIIS 2006»
13 years 3 months ago
Using KCCA for Japanese-English cross-language information retrieval and document classification
Kernel Canonical Correlation Analysis (KCCA) is a method of correlating linear relationship between two variables in a kernel defined feature space. A machine learning algorithm b...
Yaoyong Li, John Shawe-Taylor
JCP
2008
167views more  JCP 2008»
13 years 3 months ago
Accelerated Kernel CCA plus SVDD: A Three-stage Process for Improving Face Recognition
kernel canonical correlation analysis (KCCA) is a recently addressed supervised machine learning methods, which shows to be a powerful approach of extracting nonlinear features for...
Ming Li, Yuanhong Hao
ESANN
2003
13 years 5 months ago
Kernel PLS variants for regression
Abstract. We focus on covariance criteria for finding a suitable subspace for regression in a reproducing kernel Hilbert space: kernel principal component analysis, kernel partial...
Luc Hoegaerts, Johan A. K. Suykens, Joos Vandewall...
IJCNN
2006
IEEE
13 years 9 months ago
Online Kernel Canonical Correlation Analysis for Supervised Equalization of Wiener Systems
— We consider the application of kernel canonical correlation analysis (K-CCA) to the supervised equalization of Wiener systems. Although a considerable amount of research has be...
Steven Van Vaerenbergh, Javier Vía, Ignacio...