Deep er Kernels Prof. John Shawe Taylor
Yandex School of Data Analysis Conference Machine Learning: Prospects and Applications Kernels can be viewed as shallow in that learning is only applied in a single (output) layer. Recent successes with deep learning highlight the need to consider learning richer function classes. The talk will review and discuss methods that have been developed to enable richer kernel classes to be learned. While some of these methods rely on greedy procedures many are supported by
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