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NIPS
2000
15 years 8 months ago
Sparse Representation for Gaussian Process Models
We develop an approach for a sparse representation for Gaussian Process (GP) models in order to overcome the limitations of GPs caused by large data sets. The method is based on a...
Lehel Csató, Manfred Opper
BPM
2010
Springer
155views Business» more  BPM 2010»
15 years 8 months ago
PAPEL: A Language and Model for Provenance-Aware Policy Definition and Execution
The processing of data is often restricted by contractual and legal requirements for protecting privacy and IPRs. Policies provide means to control how and by whom data is processe...
Christoph Ringelstein, Steffen Staab
KDD
2007
ACM
167views Data Mining» more  KDD 2007»
16 years 7 months ago
Multiscale topic tomography
Modeling the evolution of topics with time is of great value in automatic summarization and analysis of large document collections. In this work, we propose a new probabilistic gr...
Ramesh Nallapati, Susan Ditmore, John D. Lafferty,...
COMPSAC
2008
IEEE
16 years 1 months ago
Utilising Located Functions to Model and Optimise Distributed Computations
With developments in Grid computing and Web based data storage the task of orchestrating computations is becoming ever more difficult. Identifying which of the available computati...
Stephen Crouch, Peter Henderson, Robert John Walte...
GD
2005
Springer
16 years 13 days ago
A Hybrid Model for Drawing Dynamic and Evolving Graphs
Dynamic processes frequently occur in many applications. Visualizations of dynamically evolving data, for example as part of the data analysis, are typically restricted to a cumula...
Marco Gaertler, Dorothea Wagner