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ICANN
2005
Springer
15 years 10 months ago
A Gradient Rule for the Plasticity of a Neuron's Intrinsic Excitability
While synaptic learning mechanisms have always been a core topic of neural computation research, there has been relatively little work on intrinsic learning processes, which change...
Jochen Triesch
AUSAI
1999
Springer
15 years 9 months ago
Q-Learning in Continuous State and Action Spaces
Abstract. Q-learning can be used to learn a control policy that maximises a scalar reward through interaction with the environment. Qlearning is commonly applied to problems with d...
Chris Gaskett, David Wettergreen, Alexander Zelins...
NIPS
2004
15 years 6 months ago
Supervised Graph Inference
We formulate the problem of graph inference where part of the graph is known as a supervised learning problem, and propose an algorithm to solve it. The method involves the learni...
Jean-Philippe Vert, Yoshihiro Yamanishi
ICPR
2002
IEEE
16 years 6 months ago
Relational Graph Labelling Using Learning Techniques and Markov Random Fields
This paper introduces an approach for handling complex labelling problems driven by local constraints. The purpose is illustrated by two applications: detection of the road networ...
Denis Rivière, Jean-Francois Mangin, Jean-M...
PERCOM
2007
ACM
16 years 4 months ago
MaLM: Machine Learning Middleware to Tackle Ontology Heterogeneity
We envisage pervasive computing applications to be predominantly engaged in knowledge-based interactions, where services and information will be found and exchanged based on some ...
Licia Capra