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ESANN
2007
13 years 9 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
IJIIDS
2008
201views more  IJIIDS 2008»
13 years 7 months ago
MALEF: Framework for distributed machine learning and data mining
: Growing importance of distributed data mining techniques has recently attracted attention of researchers in multiagent domain. Several agent-based application have been already c...
Jan Tozicka, Michael Rovatsos, Michal Pechoucek, S...
CDC
2009
IEEE
159views Control Systems» more  CDC 2009»
14 years 11 days ago
A distributed machine learning framework
Abstract— A distributed online learning framework for support vector machines (SVMs) is presented and analyzed. First, the generic binary classification problem is decomposed in...
Tansu Alpcan, Christian Bauckhage
CONCUR
2009
Springer
14 years 2 months ago
Encoding Asynchronous Interactions Using Open Petri Nets
Abstract. We present an encoding for (bound) processes of the asynchronous CCS with replication into open Petri nets: ordinary Petri nets equipped with a distinguished set of open ...
Paolo Baldan, Filippo Bonchi, Fabio Gadducci
LMO
1996
13 years 9 months ago
Using Metaobjects to Model Concurrent Objects with PICT
We seek to support the development of open, distributed applications from patible software abstractions. In order to rigorously specify these abstractions, we are elaborating a for...
Markus Lumpe, Jean-Guy Schneider, Oscar Nierstrasz