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ICDM
2009
IEEE
174views Data Mining» more  ICDM 2009»
14 years 2 months ago
Non-sparse Multiple Kernel Learning for Fisher Discriminant Analysis
—We consider the problem of learning a linear combination of pre-specified kernel matrices in the Fisher discriminant analysis setting. Existing methods for such a task impose a...
Fei Yan, Josef Kittler, Krystian Mikolajczyk, Muha...
LREC
2008
137views Education» more  LREC 2008»
13 years 9 months ago
Combining Multiple Models for Speech Information Retrieval
In this article we present a method for combining different information retrieval models in order to increase the retrieval performance in a Speech Information Retrieval task. The...
Muath Alzghool, Diana Inkpen
RIVF
2008
13 years 9 months ago
Simple but effective methods for combining kernels in computational biology
Complex biological data generated from various experiments are stored in diverse data types in multiple datasets. By appropriately representing each biological dataset as a kernel ...
Hiroaki Tanabe, Tu Bao Ho, Canh Hao Nguyen, Saori ...
ICDM
2003
IEEE
158views Data Mining» more  ICDM 2003»
14 years 24 days ago
Combining Multiple Weak Clusterings
A data set can be clustered in many ways depending on the clustering algorithm employed, parameter settings used and other factors. Can multiple clusterings be combined so that th...
Alexander P. Topchy, Anil K. Jain, William F. Punc...
ASPDAC
2007
ACM
116views Hardware» more  ASPDAC 2007»
13 years 11 months ago
MODLEX: A Multi Objective Data Layout EXploration Framework for Embedded Systems-on-Chip
The memory subsystem is a major contributor to the performance, power, and area of complex SoCs used in feature rich multimedia products. Hence, memory architecture of the embedded...
T. S. Rajesh Kumar, C. P. Ravikumar, R. Govindaraj...