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JMLR
2012
11 years 10 months ago
Markov Logic Mixtures of Gaussian Processes: Towards Machines Reading Regression Data
We propose a novel mixtures of Gaussian processes model in which the gating function is interconnected with a probabilistic logical model, in our case Markov logic networks. In th...
Martin Schiegg, Marion Neumann, Kristian Kersting
LION
2010
Springer
209views Optimization» more  LION 2010»
14 years 13 days ago
Feature Extraction from Optimization Data via DataModeler's Ensemble Symbolic Regression
We demonstrate a means of knowledge discovery through feature extraction that exploits the search history of an optimization run. We regress a symbolic model ensemble from optimiza...
Kalyan Veeramachaneni, Katya Vladislavleva, Una-Ma...
NIPS
2001
13 years 9 months ago
Infinite Mixtures of Gaussian Process Experts
We present an extension to the Mixture of Experts (ME) model, where the individual experts are Gaussian Process (GP) regression models. Using an input-dependent adaptation of the ...
Carl Edward Rasmussen, Zoubin Ghahramani
GLOBECOM
2008
IEEE
14 years 2 months ago
Distributed Regression in Sensor Networks with a Reduced-Order Kernel Model
Abstract—Over the past few years, wireless sensor networks received tremendous attention for monitoring physical phenomena, such as the temperature field in a given region. Appl...
Paul Honeine, Mehdi Essoloh, Cédric Richard...
ECIR
2007
Springer
13 years 9 months ago
Results Merging Algorithm Using Multiple Regression Models
: This paper describes a new algorithm for merging the results of remote collections in a distributed information retrieval environment. The algorithm makes use only of the ranks o...
Georgios Paltoglou, Michail Salampasis, Maria Satr...