Kai Bartlmae

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In this paper we introduce our departments organizational and technical infrastructure for knowledge-intensive and weak-structured processes: A framework for Knowledge Management in the case of projects in Knowledge Discovery in Databases (KDD). It is based on the experience factory approach and the method of case based reasoning. We introduce both(More)
We present the systematic method of Multitask Learning for incorporating prior knowledge (hints) into the inductive learning system of neural networks. Multitask Learning is an inductive transfer method which uses domain information about related tasks as inductive bias to guide the learning process towards better solutions of the main problem. These tasks(More)
In this paper we propose a framework for estimation and quality control of conditional neural network volatility models for market risk management. In a first step, we derive a conditional volatility model based on gaussian mixture densities, that can be used with linear or neural regression models (extendable even to rule systems or decision trees). In a(More)
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