395 search results - page 15 / 79 » Learning to rank with partially-labeled data |
ICML
2005
IEEE
16 years 16 days ago
2005
IEEE
We investigate using gradient descent methods for learning ranking functions; we propose a simple probabilistic cost function, and we introduce RankNet, an implementation of these...
100
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ICML
2010
IEEE
15 years 24 days ago
2010
IEEE
This paper introduces two new methods for label ranking based on a probabilistic model of ranking data, called the Plackett-Luce model. The idea of the first method is to use the ...
109
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KDD
2008
ACM
16 years 4 days ago
2008
ACM
We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
DIS
2009
Springer
15 years 6 months ago
2009
Springer
Within-network regression addresses the task of regression in partially labeled networked data where labels are sparse and continuous. Data for inference consist of entities associ...
91
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ESANN
2004
15 years 1 months ago
2004
Input feature ranking and selection represent a necessary preprocessing stage in classification, especially when one is required to manage large quantities of data. We introduce a ...