91 search results - page 2 / 19 » Conditional Models for Non-smooth Ranking Loss Functions |
RECSYS
2010
ACM
13 years 4 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 6 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 10 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
13 years 11 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 6 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...