53 search results - page 1 / 11 » An Efficient Boosting Algorithm for Combining Preferences |
ICML
1998
IEEE
14 years 5 months ago
1998
IEEE
We study the problem of learning to accurately rank a set of objects by combining a given collection of ranking or preference functions. This problem of combining preferences aris...
KDD
2001
ACM
14 years 4 months ago
2001
ACM
In this paper, we propose a general framework for distributed boosting intended for efficient integrating specialized classifiers learned over very large and distributed homogeneo...
ICPR
2008
IEEE
14 years 5 months ago
2008
IEEE
Two major challenges in collaborative filtering are the efficiency of the algorithms and the quality of the recommendations. A variety of machine learning methods have been applie...
NIPS
2004
13 years 5 months ago
2004
In this paper we propose to combine two powerful ideas, boosting and manifold learning. On the one hand, we improve ADABOOST by incorporating knowledge on the structure of the dat...
ESWA
2008
13 years 4 months ago
2008
Recommender systems base their operation on past user ratings over a collection of items, for instance, books, CDs, etc. Collaborative filtering (CF) is a successful recommendatio...