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ICML
2005
IEEE
16 years 7 months ago
Learning Gaussian processes from multiple tasks
We consider the problem of multi-task learning, that is, learning multiple related functions. Our approach is based on a hierarchical Bayesian framework, that exploits the equival...
Kai Yu, Volker Tresp, Anton Schwaighofer
WSC
2008
15 years 9 months ago
A proposal for coordinator control recipe in a batch process
In this work, we propose a coordinator control recipe in the context of a batch process with the use of elements of petri nets and some techniques associated with non linear contr...
Jose Francisco, Briones de la Torre, Antonio Espu&...
NIPS
2004
15 years 8 months ago
Semi-supervised Learning via Gaussian Processes
We present a probabilistic approach to learning a Gaussian Process classifier in the presence of unlabeled data. Our approach involves a "null category noise model" (NCN...
Neil D. Lawrence, Michael I. Jordan
NIPS
2000
15 years 8 months ago
Mixtures of Gaussian Processes
We introduce the mixture of Gaussian processes (MGP) model which is useful for applications in which the optimal bandwidth of a map is input dependent. The MGP is derived from the...
Volker Tresp
CAISE
2008
Springer
15 years 8 months ago
A Tool for Process Merging in Business-Driven Development
Abstract. Business-driven development favors the construction of process modifferent abstraction levels and by different people. As a consequence, there is a demand for consolidati...
Jochen Malte Küster, Christian Gerth, Alexand...