354 search results - page 3 / 71 » Top-k learning to rank: labeling, ranking and evaluation |
AAAI
2011
12 years 5 months ago
2011
Inspired by “GoogleTM Sets” and Bayesian sets, we consider the problem of retrieving complex objects and relations among them, i.e., ground atoms from a logical concept, given...
AI
2008
Springer
13 years 5 months ago
2008
Springer
Preference learning is a challenging problem that involves the prediction of complex structures, such as weak or partial order relations, rather than single values. In the recent ...
IDA
2005
Springer
13 years 10 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...
ECML
2006
Springer
13 years 9 months ago
2006
Springer
Abstract. We propose a novel active learning strategy based on the compression framework of [9] for label ranking functions which, given an input instance, predict a total order ov...
JMLR
2012
11 years 7 months ago
2012
We consider the task of devising large-margin based surrogate losses for the learning to rank problem. In this learning to rank setting, the traditional hinge loss for structured ...