91 search results - page 2 / 19 » Conditional Models for Non-smooth Ranking Loss Functions |
RECSYS
2010
ACM
13 years 5 months ago
2010
ACM
A ranking approach, ListRank-MF, is proposed for collaborative filtering that combines a list-wise learning-to-rank algorithm with matrix factorization (MF). A ranked list of item...
AI
2006
Springer
13 years 7 months ago
2006
Springer
The Spohnian paradigm of ranking functions is in many respects like an order-of-magnitude reverse of subjective probability theory. Unlike probabilities, however, ranking function...
ECML
2006
Springer
13 years 11 months ago
2006
Springer
Abstract. In this paper, we propose a new method for learning to rank. `Ranking SVM' is a method for performing the task. It formulizes the problem as that of binary classific...
COLT
2005
Springer
14 years 1 months ago
2005
Springer
The problem of ranking, in which the goal is to learn a real-valued ranking function that induces a ranking or ordering over an instance space, has recently gained attention in mac...
CORR
2006
Springer
13 years 7 months ago
2006
Springer
We consider the problem of decision-making with side information and unbounded loss functions. Inspired by probably approximately correct learning model, we use a slightly differe...