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8

ALT
2005
Springer

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Mixture of Vector Experts

14 years 2 months ago

Mixture of Vector Experts

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Abstract. We describe and analyze an algorithm for predicting a sequence of n-dimensional binary vectors based on a set of experts making vector predictions in [0, 1]n . We measure the loss of individual predictions by the 2-norm between the actual outcome vector and the prediction. The loss of an expert is then the sum of the losses experienced on individual trials. We obtain bounds for the loss of our expert algorithm in terms of the loss of the best expert analogous to the well-known results for scalar experts making real-valued predictions of a binary outcome.

Matthew Henderson, John Shawe-Taylor, Janez Zerovn

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Actual Outcome Vector | ALT 2005 | Experts Making Vector | Machine Learning | N-dimensional Binary Vectors |

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Added	14 Mar 2010
Updated	14 Mar 2010
Type	Conference
Year	2005
Where	ALT
Authors	Matthew Henderson, John Shawe-Taylor, Janez Zerovnik

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