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Learning distance functions In Sui CS395T Visual Recognition and Search The University of Texas at Austin Outline Introduction Learning one Mahalanobis distance metric Learning multiple distance functions
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Learning distance functions form is a document used to gather information about the distance functions used in machine learning algorithms.
Data scientists, machine learning engineers, and researchers who work with distance functions in their models are required to file the learning distance functions form.
The form typically requires information about the specific distance functions used, their parameters, and any modifications made to them during model training.
The purpose of the learning distance functions form is to ensure transparency and reproducibility in machine learning projects by documenting the choices made regarding distance functions.
Information such as the type of distance functions used, their mathematical formulation, any hyperparameters involved, and any adjustments made to them during training must be reported on the form.
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