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ICPR
2010
IEEE
15 years 11 months ago
Learning an Efficient and Robust Graph Matching Procedure for Specific Object Recognition
We present a fast and robust graph matching approach for 2D specific object recognition in images. From a small number of training images, a model graph of the object to learn is a...
Jerome Revaud, Guillaume Lavoue, Yasuo Ariki, Atil...
ILP
2003
Springer
16 years 7 days 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
FLAIRS
2001
15 years 8 months ago
Graph-Based Concept Learning
We introduce the graph-based relational concept learner SubdueCL. We start with a brief description of other graph-based learning systems: the Galois lattice, Conceptual Graphs, a...
Jesus A. Gonzalez, Lawrence B. Holder, Diane J. Co...
SIGIR
2008
ACM
15 years 7 months ago
Learning query intent from regularized click graphs
This work presents the use of click graphs in improving query intent classifiers, which are critical if vertical search and general-purpose search services are to be offered in a ...
Xiao Li, Ye-Yi Wang, Alex Acero
IJAR
2006
89views more  IJAR 2006»
15 years 7 months ago
Learning probabilistic decision graphs
Probabilistic decision graphs (PDGs) are a representation language for probability distributions based on binary decision diagrams. PDGs can encode (context-specific) independence...
Manfred Jaeger, Jens D. Nielsen, Tomi Silander