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We examine the problem of classifying biological sequences, and in particular the challenge of generalizing to novel input data. The high dimensionality of sequence results in an extremely sparsely populated input space. This motivates a need for regularization (a form of inductive bias), in order to achieve generalization. We discuss regularization in the context of regular Neural Networks and Deep...
We examine the problem of classifying biological sequences, and in particular the challenge of generalizing results to novel input data. We observe that the high-dimensionality of sequence data representations results in an extremely sparsely populated input space. This motivates a need for regularization (a form of inductive bias), in order to achieve generalization. We discuss regularization in...
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