99 search results - page 6 / 20 » Ranking and Scoring Using Empirical Risk Minimization |
ICML
2009
IEEE
15 years 10 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...
IDA
2005
Springer
15 years 3 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...
CIKM
2001
Springer
15 years 2 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 ...
JMLR
2010
14 years 4 months 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...
NIPS
2003
14 years 11 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...