UAI
2008
13 years 6 months ago
2008
In many machine learning problems, labeled training data is limited but unlabeled data is ample. Some of these problems have instances that can be factored into multiple views, ea...
CIKM
2008
Springer
13 years 6 months ago
2008
Springer
This paper points out that many machine learning problems in IR should be and can be formalized in a novel way, referred to as `group-based learning'. In group-based learning...
MCS
2001
Springer
13 years 9 months ago
2001
Springer
Using an ensemble of classifiers instead of a single classifier has been shown to improve generalization performance in many machine learning problems [4, 16]. However, the exten...
CEC
2005
IEEE
13 years 10 months ago
2005
IEEE
Co-evolutionary algorithms (CEAs) have been applied to optimization and machine learning problems with often mediocre results. One of the causes for the unfulfilled expectations i...
KDD
2007
ACM
14 years 5 months ago
2007
ACM
A wide variety of machine learning problems can be described as minimizing a regularized risk functional, with different algorithms using different notions of risk and different r...
ICML
2008
IEEE
14 years 5 months ago
2008
IEEE
In real-world machine learning problems, it is very common that part of the input feature vector is incomplete: either not available, missing, or corrupted. In this paper, we pres...