159 search results - page 24 / 32 » Margin Maximizing Loss Functions |
76
Voted
PAMI
2008
14 years 11 months ago
2008
In this paper, we develop a new effective multiple kernel learning algorithm. First, we map the input data into m different feature spaces by m empirical kernels, where each genera...
114
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JMLR
2008
14 years 11 months ago
2008
We consider the problem of learning classifiers in structured domains, where some objects have a subset of features that are inherently absent due to complex relationships between...
112
Voted
SISAP
2008
IEEE
15 years 6 months ago
2008
IEEE
There are several pieces of information that can be utilized in order to improve the efficiency of similarity searches on high-dimensional data. The most commonly used information...
DAC
2009
ACM
15 years 4 months ago
2009
ACM
Process scaling has given designers billions of transistors to work with. As feature sizes near the atomic scale, extensive variation and wearout inevitably make margining unecono...
110
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IJPRAI
2010
14 years 10 months ago
2010
: AUC-SVM directly maximizes the area under the ROC curve (AUC) through minimizing its hinge loss relaxation, and the decision function is determined by those support vector sample...