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ECML
2004
Springer
13 years 11 months ago
Experiments in Value Function Approximation with Sparse Support Vector Regression
Abstract. We present first experiments using Support Vector Regression as function approximator for an on-line, sarsa-like reinforcement learner. To overcome the batch nature of S...
Tobias Jung, Thomas Uthmann
IPMI
2009
Springer
13 years 10 months ago
Discovering Sparse Functional Brain Networks Using Group Replicator Dynamics (GRD)
Functional magnetic resonance imaging (fMRI) has become increasingly used for studying functional integration of the brain. However, the large inter-subject variability in function...
Bernard Ng, Rafeef Abugharbieh, Martin J. McKeown
SIAMJO
2008
108views more  SIAMJO 2008»
13 years 5 months ago
Sparse SOS Relaxations for Minimizing Functions that are Summations of Small Polynomials
This paper discusses how to find the global minimum of functions that are summations of small polynomials ("small" means involving a small number of variables). Some spa...
Jiawang Nie, James Demmel
NIPS
2008
13 years 7 months ago
Sparse Convolved Gaussian Processes for Multi-output Regression
We present a sparse approximation approach for dependent output Gaussian processes (GP). Employing a latent function framework, we apply the convolution process formalism to estab...
Mauricio Alvarez, Neil D. Lawrence
DEXA
2008
Springer
123views Database» more  DEXA 2008»
13 years 7 months ago
Evolutionary Clustering in Description Logics: Controlling Concept Formation and Drift in Ontologies
Abstract. We present a method based on clustering techniques to detect concept drift or novelty in a knowledge base expressed in Description Logics. The method exploits an effectiv...
Nicola Fanizzi, Claudia d'Amato, Floriana Esposito