Sciweavers

Share
JMLR
2008
139views more  JMLR 2008»
8 years 6 months ago
Regularization on Graphs with Function-adapted Diffusion Processes
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 ...
Arthur D. Szlam, Mauro Maggioni, Ronald R. Coifman
NIPS
2003
8 years 7 months ago
Error Bounds for Transductive Learning via Compression and Clustering
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...
Philip Derbeko, Ran El-Yaniv, Ron Meir
IJCNLP
2005
Springer
8 years 12 months ago
Mining Inter-Entity Semantic Relations Using Improved Transductive Learning
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...
Zhu Zhang
MLDM
2007
Springer
9 years 17 days ago
Transductive Learning from Relational Data
Transduction is an inference mechanism “from particular to particular”. Its application to classification tasks implies the use of both labeled (training) data and unlabeled (...
Michelangelo Ceci, Annalisa Appice, Nicola Barile,...
COLT
2007
Springer
9 years 19 days ago
Transductive Rademacher Complexity and Its Applications
We present data-dependent error bounds for transductive learning based on transductive Rademacher complexity. For specific algorithms we provide bounds on their Rademacher complex...
Ran El-Yaniv, Dmitry Pechyony
PKDD
2009
Springer
117views Data Mining» more  PKDD 2009»
9 years 1 months ago
New Regularized Algorithms for Transductive Learning
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...
Partha Pratim Talukdar, Koby Crammer
ICML
2003
IEEE
9 years 7 months ago
Transductive Learning via Spectral Graph Partitioning
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...
Thorsten Joachims
books