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ICML
2005
IEEE
14 years 11 months ago
Semi-supervised graph clustering: a kernel approach
Semi-supervised clustering algorithms aim to improve clustering results using limited supervision. The supervision is generally given as pairwise constraints; such constraints are...
Brian Kulis, Sugato Basu, Inderjit S. Dhillon, Ray...
ICCV
2003
IEEE
14 years 3 months ago
Edit Distance From Graph Spectra
This paper is concerned with computing graph edit distance. One of the criticisms that can be leveled at existing methods for computing graph edit distance is that it lacks the fo...
Antonio Robles-Kelly, Edwin R. Hancock
COMPGEOM
2004
ACM
14 years 3 months ago
The geometric thickness of low degree graphs
We prove that the geometric thickness of graphs whose maximum degree is no more than four is two. In our proofs, we present a space and time efficient embedding technique for gra...
Christian A. Duncan, David Eppstein, Stephen G. Ko...
NIPS
2004
13 years 11 months ago
Nonparametric Transforms of Graph Kernels for Semi-Supervised Learning
We present an algorithm based on convex optimization for constructing kernels for semi-supervised learning. The kernel matrices are derived from the spectral decomposition of grap...
Xiaojin Zhu, Jaz S. Kandola, Zoubin Ghahramani, Jo...
IJRR
2006
116views more  IJRR 2006»
13 years 10 months ago
The Graph SLAM Algorithm with Applications to Large-Scale Mapping of Urban Structures
This article presents GraphSLAM, a unifying algorithm for the offline SLAM problem. GraphSLAM is closely related to a recent sequence of research papers on applying optimization t...
Sebastian Thrun, Michael Montemerlo