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A time series can often be characterized using machine learning techniques, which require feature vectors as input. The quality of the feature vectors reflects the accuracy of the utilized machine learning techniques. We propose a method for combining features extracted from two popular...
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A common phenomena in modern recommendation systems is the use of feedback from one user to infer the ‘value’ of an item to other users. This results in an exploration vs. exploitation trade-off, in which items of possibly low value have to be presented to users in order to ascertain their...
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We present a novel technique for cardinality-constrained index-tracking, a common task in the financial industry. Our approach is based on market graph models. We model our reference indices as market graphs and express the index-tracking problem as a quadratic K-medoids clustering problem. We...
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, we first propose a novel algorithm, which is a variant of Tarjan’s algorithm that simultaneously finds the SCCs and their … discounted MDPs using value iteration (VI) algorithm based on a list of state-action successors. Finally, a robotic motion …
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