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NIPS
1997
15 years 5 months ago
Learning Generative Models with the Up-Propagation Algorithm
Up-propagation is an algorithm for inverting and learning neural network generative models. Sensory input is processed by inverting a model that generates patterns from hidden var...
Jong-Hoon Oh, H. Sebastian Seung
CINQ
2004
Springer
182views Database» more  CINQ 2004»
15 years 8 months ago
Mining Constrained Graphs: The Case of Workflow Systems
Abstract. Constrained graphs are directed graphs describing the control flow of processes models. In such graphs, nodes represent activities involved in the process, and edges the ...
Gianluigi Greco, Antonella Guzzo, Giuseppe Manco, ...
FORTE
2004
15 years 6 months ago
How Synchronisation Strategy Approximation in PEPA Implementations Affects Passage Time Performance Results
Passage time densities are useful performance measurements in stochastic systems. With them the modeller can extract probabilistic quality-of-service guarantees such as: the proba...
Jeremy T. Bradley, Stephen T. Gilmore, Nigel Thoma...
BDA
2001
15 years 6 months ago
Query-Driven Knowledge Discovery via OLAP manipulations
We study KDD (Knowledge Discovery in Databases) processes on OLAP (multidimensional and multilevel) data from a query point of view. Focusing on association rule mining, we consid...
Jean-François Boulicaut, Patrick Marcel, Ch...
IADIS
2003
15 years 6 months ago
Informatization and E-Business Model Application for Distributed Data Mining Using Mobile Agents
Distributed data mining (DDM) is the semi-automatic pattern extraction of distributed data sources. The next generation of the data mining studies will be distributed data mining ...
Ezendu Ifeanyi Ariwa, Mohamed B. Senousy, Mohamed ...