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Multi-Task Learning For Option Pricing

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Table 1: Analysis of variance results obtained when comparing the generalization perfor- perfor-mance of single models trained without bias learning with models obtained when using affine manifolds and simultaneously training N tasks, each having a trainin
Figure 1: Generalization mean squared errors measured from January 1989 to December 1993 using on the one hand a model trained with no bias learning and on the other hand the affine manifold learning method trained on 3 tasks each using 6 months training s

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