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» Learning to rank with multiple objective functions
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CVPR
2010
IEEE
15 years 1 months ago
On the design of robust classifiers for computer vision
The design of robust classifiers, which can contend with the noisy and outlier ridden datasets typical of computer vision, is studied. It is argued that such robustness requires l...
Hamed Masnadi-Shirazi, Nuno Vasconcelos, Vijay Mah...
SIGIR
2010
ACM
14 years 9 months ago
Optimal meta search results clustering
By analogy with merging documents rankings, the outputs from multiple search results clustering algorithms can be combined into a single output. In this paper we study the feasibi...
Claudio Carpineto, Giovanni Romano
IJON
2007
99views more  IJON 2007»
14 years 9 months ago
A relative trust-region algorithm for independent component analysis
In this paper we present a method of parameter optimization, relative trust-region learning, where the trust-region method and the relative optimization [21] are jointly exploited...
Heeyoul Choi, Seungjin Choi
NIPS
2000
14 years 11 months ago
One Microphone Source Separation
Source separation, or computational auditory scene analysis, attempts to extract individual acoustic objects from input which contains a mixture of sounds from different sources, ...
Sam T. Roweis
ICCV
2009
IEEE
14 years 7 months ago
Selection and context for action recognition
Recognizing human action in non-instrumented video is a challenging task not only because of the variability produced by general scene factors like illumination, background, occlu...
Dong Han, Liefeng Bo, Cristian Sminchisescu