99 search results - page 6 / 20 » Ranking and Scoring Using Empirical Risk Minimization |
170
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ICML
2009
IEEE
16 years 6 months ago
2009
IEEE
We propose a new penalty function which, when used as regularization for empirical risk minimization procedures, leads to sparse estimators. The support of the sparse vector is ty...
174
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IDA
2005
Springer
15 years 11 months ago
2005
Springer
We consider the problem of learning a ranking function, that is a mapping from instances to rankings over a finite number of labels. Our learning method, referred to as ranking by...
141
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CIKM
2001
Springer
15 years 10 months ago
2001
Springer
Given the ranked lists of documents returned by multiple search engines in response to a given query, the problem of metasearch is to combine these lists in a way which optimizes ...
170
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JMLR
2010
15 years 20 days ago
2010
The problem of characterizing learnability is the most basic question of statistical learning theory. A fundamental and long-standing answer, at least for the case of supervised c...
154
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NIPS
2003
15 years 7 months ago
2003
The area under an ROC curve (AUC) is a criterion used in many applications to measure the quality of a classification algorithm. However, the objective function optimized in most...