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FOCS
2009
IEEE
15 years 4 months ago
(Meta) Kernelization
Polynomial time preprocessing to reduce instance size is one of the most commonly deployed heuristics to tackle computationally hard problems. In a parameterized problem, every in...
Hans L. Bodlaender, Fedor V. Fomin, Daniel Lokshta...
ICIP
2010
IEEE
14 years 7 months ago
Image partitioning with kernel mapping and graph cuts
A novel multiregion graph cut image partitioning method combined with kernel mapping is presented. A kernel function transforms implicitly the image data into data of a higher dim...
Mohamed Ben Salah, Amar Mitiche, Ismail Ben Ayed
GBRPR
2007
Springer
15 years 1 months ago
Image Classification Using Marginalized Kernels for Graphs
We propose in this article an image classification technique based on kernel methods and graphs. Our work explores the possibility of applying marginalized kernels to image process...
Emanuel Aldea, Jamal Atif, Isabelle Bloch
ICML
2005
IEEE
15 years 10 months ago
Optimal assignment kernels for attributed molecular graphs
We propose a new kernel function for attributed molecular graphs, which is based on the idea of computing an optimal assignment from the atoms of one molecule to those of another ...
Andreas Zell, Florian Sieker, Holger Fröhlich...
ICML
2005
IEEE
15 years 10 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...