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ICPR
2010
IEEE
15 years 1 months ago
Kernel-Based Implicit Regularization of Structured Objects
Weighted graph regularization provides a rich framework that allows to regularize functions defined over the vertices of a weighted graph. Until now, such a framework has been only...
François-Xavier Dupé, Sébastien Bougleux, Luc B...
ILP
2003
Springer
15 years 3 months ago
Graph Kernels and Gaussian Processes for Relational Reinforcement Learning
RRL is a relational reinforcement learning system based on Q-learning in relational state-action spaces. It aims to enable agents to learn how to act in an environment that has no ...
Thomas Gärtner, Kurt Driessens, Jan Ramon
WABI
2009
Springer
162views Bioinformatics» more  WABI 2009»
15 years 4 months ago
Aligning Biomolecular Networks Using Modular Graph Kernels
Comparative analysis of biomolecular networks constructed using measurements from different conditions, tissues, and organisms offer a powerful approach to understanding the stru...
Fadi Towfic, M. Heather West Greenlee, Vasant Hona...
CIKM
2009
Springer
15 years 4 months ago
Learning to rank graphs for online similar graph search
Many applications in structure matching require the ability to search for graphs that are similar to a query graph, i.e., similarity graph queries. Prior works, especially in chem...
Bingjun Sun, Prasenjit Mitra, C. Lee Giles
SODA
2010
ACM
261views Algorithms» more  SODA 2010»
15 years 7 months ago
Bidimensionality and Kernels
Bidimensionality theory appears to be a powerful framework in the development of meta-algorithmic techniques. It was introduced by Demaine et al. [J. ACM 2005 ] as a tool to obtai...
Fedor V. Fomin, Daniel Lokshtanov, Saket Saurabh, ...