Kai Bartlmae

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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)
  • Kai Bartlmae
  • 2009 International Conference on Business…
  • 2009
In this paper we introduce a framework for constructing portfolios, addressing two of the major problems of classical mean-variance optimization in practice: Low diversification and sensitivity to information ambiguity. In order to address these issues, we incorporate a prior regarding investors preferences as well as using a bootstrapping method to(More)
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