%0 Generic %1 duvenaud2013structure %A Duvenaud, David %A Lloyd, James Robert %A Grosse, Roger %A Tenenbaum, Joshua B. %A Ghahramani, Zoubin %D 2013 %K statistics %T Structure Discovery in Nonparametric Regression through Compositional Kernel Search %U http://arxiv.org/abs/1302.4922 %X Despite its importance, choosing the structural form of the kernel in nonparametric regression remains a black art. We define a space of kernel structures which are built compositionally by adding and multiplying a small number of base kernels. We present a method for searching over this space of structures which mirrors the scientific discovery process. The learned structures can often decompose functions into interpretable components and enable long-range extrapolation on time-series datasets. Our structure search method outperforms many widely used kernels and kernel combination methods on a variety of prediction tasks.

@misc{duvenaud2013structure, abstract = {Despite its importance, choosing the structural form of the kernel in nonparametric regression remains a black art. We define a space of kernel structures which are built compositionally by adding and multiplying a small number of base kernels. We present a method for searching over this space of structures which mirrors the scientific discovery process. The learned structures can often decompose functions into interpretable components and enable long-range extrapolation on time-series datasets. Our structure search method outperforms many widely used kernels and kernel combination methods on a variety of prediction tasks.}, added-at = {2020-06-28T21:48:10.000+0200}, author = {Duvenaud, David and Lloyd, James Robert and Grosse, Roger and Tenenbaum, Joshua B. and Ghahramani, Zoubin}, biburl = {https://www.bibsonomy.org/bibtex/2ca6a2d6849dc71fb989360e97d19b3e6/cmcneile}, description = {Structure Discovery in Nonparametric Regression through Compositional Kernel Search}, interhash = {ebe1cd2574f02529589660d69f7c97f4}, intrahash = {ca6a2d6849dc71fb989360e97d19b3e6}, keywords = {statistics}, note = {cite arxiv:1302.4922Comment: 9 pages, 7 figures, To appear in proceedings of the 2013 International Conference on Machine Learning}, timestamp = {2020-06-28T21:48:10.000+0200}, title = {Structure Discovery in Nonparametric Regression through Compositional Kernel Search}, url = {http://arxiv.org/abs/1302.4922}, year = 2013 }