155 search results - page 10 / 31 » On learning linear ranking functions for beam search |
ICML
2003
IEEE
14 years 8 months ago
2003
IEEE
We investigate how stack filter function classes like weighted order statistics can be applied to classification problems. This leads to a new design criteria for linear classifie...
IPM
2008
13 years 7 months ago
2008
Many machine learning technologies such as support vector machines, boosting, and neural networks have been applied to the ranking problem in information retrieval. However, since...
WWW
2011
ACM
13 years 2 months ago
2011
ACM
Gradient Boosted Regression Trees (GBRT) are the current state-of-the-art learning paradigm for machine learned websearch ranking — a domain notorious for very large data sets. ...
CC
2010
Springer
13 years 5 months ago
2010
Springer
We prove that the concept class of disjunctions cannot be pointwise approximated by linear combinations of any small set of arbitrary real-valued functions. That is, suppose that t...
AAAI
2011
12 years 7 months ago
2011
We propose CCRank, the first parallel algorithm for learning to rank, targeting simultaneous improvement in learning accuracy and efficiency. CCRank is based on cooperative coev...