Dynamic Bayesian networks are structured representations of stochastic processes. Despite their structure, exact inference in DBNs is generally intractable. One approach to approx...
In recent years, privacy preserving data mining has become very important because of the proliferation of large amounts of data on the internet. Many data sets are inherently high...
We present a new approach for dealing with distribution change and concept drift when learning from data sequences that may vary with time. We use sliding windows whose size, inst...
Since the description of the Semantic Web paradigm in 2001, technology has been proposed to allow its deployment and use. However, there is not yet any large and widely deployed s...
In many real world planning scenarios, agents often do not have enough resources to achieve all of their goals. Consequently, they are forced to find plans that satisfy only a sub...
Menkes van den Briel, Romeo Sanchez Nigenda, Minh ...