Deep-er Kernels

Prof. John Shawe-Taylor
UK, Centre for Computation Statistics and Machine Learning at University College London
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 statistical learning analyses and/or convergence bounds. The talk will highlight the trade-offs involved and the potential for further research on this topic.