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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...
TIP
2011
164views more  TIP 2011»
14 years 4 months ago
Multiregion Image Segmentation by Parametric Kernel Graph Cuts
Abstract—The purpose of this study is to investigate multiregion graph cut image partitioning via kernel mapping of the image data. The image data is transformed implicitly by a ...
Mohamed Ben Salah, Amar Mitiche, Ismail Ben Ayed
BMCBI
2008
149views more  BMCBI 2008»
14 years 9 months ago
All-paths graph kernel for protein-protein interaction extraction with evaluation of cross-corpus learning
Background: Automated extraction of protein-protein interactions (PPI) is an important and widely studied task in biomedical text mining. We propose a graph kernel based approach ...
Antti Airola, Sampo Pyysalo, Jari Björne, Tap...
BMCBI
2010
86views more  BMCBI 2010»
14 years 10 months ago
Reaction graph kernels predict EC numbers of unknown enzymatic reactions in plant secondary metabolism
Background: Understanding of secondary metabolic pathway in plant is essential for finding druggable candidate enzymes. However, there are many enzymes whose functions are not yet...
Hiroto Saigo, Masahiro Hattori, Hisashi Kashima, K...
ILP
2003
Springer
15 years 2 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