ICANN
2009
Springer
13 years 9 months ago
2009
Springer
Abstract. This paper studies a risk minimization approach to estimate a transformation model from noisy observations. It is argued that transformation models are a natural candidat...
IIR
2010
13 years 9 months ago
2010
We present four new feature selection methods for ordinal regression and test them against four different baselines on two large datasets of product reviews.
NECO
2007
13 years 11 months ago
2007
In this paper, we propose two new support vector approaches for ordinal regression, which optimize multiple thresholds to define parallel discriminant hyperplanes for the ordinal...
ICDM
2005
IEEE
14 years 5 months ago
2005
IEEE
The preference model introduced in this paper gives a natural framework and a principled solution for a broad class of supervised learning problems with structured predictions, su...
IJCNN
2008
IEEE
14 years 5 months ago
2008
IEEE
— Ordinal regression is an important type of learning, which has properties of both classification and regression. Here we describe an effective approach to adapt a traditional ...
SAC
2010
ACM
14 years 6 months ago
2010
ACM
Ordinal regression (also known as ordinal classification) is a supervised learning task that consists of automatically determining the implied rating of a data item on a fixed, ...
WWW
2005
ACM
15 years 3 days ago
2005
ACM
This paper is concerned with the problem of definition search. Specifically, given a term, we are to retrieve definitional excerpts of the term and rank the extracted excerpts acc...
ICML
2005
IEEE
15 years 7 days ago
2005
IEEE
In this paper, we propose two new support vector approaches for ordinal regression, which optimize multiple thresholds to define parallel discriminant hyperplanes for the ordinal ...