JMLR
2008
13 years 4 months ago
2008
Harmonic analysis and diffusion on discrete data has been shown to lead to state-of-theart algorithms for machine learning tasks, especially in the context of semi-supervised and ...
NIPS
2003
13 years 5 months ago
2003
This paper is concerned with transductive learning. Although transduction appears to be an easier task than induction, there have not been many provably useful algorithms and boun...
IJCNLP
2005
Springer
13 years 10 months ago
2005
Springer
This paper studies the problem of mining relational data hidden in natural language text. In particular, it approaches the relation classification problem with the strategy of tra...
MLDM
2007
Springer
13 years 10 months ago
2007
Springer
Transduction is an inference mechanism “from particular to particular”. Its application to classification tasks implies the use of both labeled (training) data and unlabeled (...
COLT
2007
Springer
13 years 10 months ago
2007
Springer
We present data-dependent error bounds for transductive learning based on transductive Rademacher complexity. For specific algorithms we provide bounds on their Rademacher complex...
PKDD
2009
Springer
13 years 11 months ago
2009
Springer
Abstract. We propose a new graph-based label propagation algorithm for transductive learning. Each example is associated with a vertex in an undirected graph and a weighted edge be...
ICML
2003
IEEE
14 years 5 months ago
2003
IEEE
We present a new method for transductive learning, which can be seen as a transductive version of the k nearest-neighbor classifier. Unlike for many other transductive learning me...