99 search results - page 9 / 20 » Ranking and Scoring Using Empirical Risk Minimization |
155
Voted
SIGMOD
2009
ACM
15 years 9 months ago
2009
ACM
In the rank join problem we are given a relational join R1 1 R2 and a function that assigns numeric scores to the join tuples, and the goal is to return the tuples with the highes...
108
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IJCAI
2001
14 years 11 months ago
2001
For many supervised learning tasks it is very costly to produce training data with class labels. Active learning acquires data incrementally, at each stage using the model learned...
BMCBI
2008
14 years 9 months ago
2008
Background: When analyzing microarray data a primary objective is often to find differentially expressed genes. With empirical Bayes and penalized t-tests the sample variances are...
ACL
2006
14 years 11 months ago
2006
When training the parameters for a natural language system, one would prefer to minimize 1-best loss (error) on an evaluation set. Since the error surface for many natural languag...
ICML
2010
IEEE
14 years 10 months ago
2010
IEEE
We present a theoretical analysis of supervised ranking, providing necessary and sufficient conditions for the asymptotic consistency of algorithms based on minimizing a surrogate...