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ICML
2003
IEEE
15 years 10 months ago
Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions
An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, wit...
Xiaojin Zhu, Zoubin Ghahramani, John D. Lafferty
CVPR
2009
IEEE
16 years 5 months ago
A Tensor-Based Algorithm for High-Order Graph Matching
This paper addresses the problem of establishing correspondences between two sets of visual features using higher-order constraints instead of the unary or pairwise ones used in...
Francis R. Bach, In-So Kweon, Jean Ponce, Olivier ...
AAAI
2006
14 years 11 months ago
Learning Representation and Control in Continuous Markov Decision Processes
This paper presents a novel framework for simultaneously learning representation and control in continuous Markov decision processes. Our approach builds on the framework of proto...
Sridhar Mahadevan, Mauro Maggioni, Kimberly Fergus...
ML
2010
ACM
193views Machine Learning» more  ML 2010»
14 years 4 months ago
On the eigenvectors of p-Laplacian
Spectral analysis approaches have been actively studied in machine learning and data mining areas, due to their generality, efficiency, and rich theoretical foundations. As a natur...
Dijun Luo, Heng Huang, Chris H. Q. Ding, Feiping N...
ICDM
2009
IEEE
171views Data Mining» more  ICDM 2009»
14 years 7 months ago
Hybrid Clustering by Integrating Text and Citation Based Graphs in Journal Database Analysis
We propose a hybrid clustering strategy by integrating heterogeneous information sources as graphs. The hybrid clustering method is extended on the basis of modularity based Louva...
Xinhai Liu, Shi Yu, Yves Moreau, Frizo A. L. Janss...