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ESANN
2007
15 years 8 months ago
How to process uncertainty in machine learning?
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
Barbara Hammer, Thomas Villmann
IMAGING
2003
15 years 8 months ago
Group Theoretical Invariants in Color Image Processing
Many image formation processes are complex interactions of several sub-processes and the analysis of the resulting images requires often to separate the influence of these sub-pr...
Reiner Lenz, Linh Viet Tran, Thanh Hai Bui
APVIS
2009
15 years 8 months ago
Visualization of signal transduction processes in the crowded environment of the cell
In this paper, we propose a stochastic simulation to model and analyze cellular signal transduction. The high number of objects in a simulation requires advanced visualization tec...
Martin Falk, Michael Klann, Matthias Reuss, Thomas...
ENTCS
2006
114views more  ENTCS 2006»
15 years 6 months ago
What is algebraic in process theory?
This is an extended version of an essay with the same title that I wrote for the workshop Algebraic Process Calculi: The First Twenty Five Years and Beyond, held in Bertinoro, Ita...
Bas Luttik
JMLR
2008
159views more  JMLR 2008»
15 years 6 months ago
Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies
When monitoring spatial phenomena, which can often be modeled as Gaussian processes (GPs), choosing sensor locations is a fundamental task. There are several common strategies to ...
Andreas Krause, Ajit Paul Singh, Carlos Guestrin