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Topic Suggestions
Reading suggestions:
(Papers that have been presented previously marked by strikethrough)
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Book by Grace Wahba.
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Convergence guarantees for kernel-based quadrature rules in misspecified settings Motonobu Kanagawa, Bharath Sriperumbudur, Kenji Fukumizu. arxiv
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Universality of Mallows' and degeneracy of Kendall's kernels for rankings. Horia Mania, Aaditya Ramdas, Martin J. Wainwright, Michael I. Jordan, Benjamin Recht. arxiv
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Joint quantile regression in vector-valued RKHSs, Maxime Sangnier, Olivier Fercoq, Florence d’Alché-Buc, pdf -
I. Steinwart, P. Thomann, and N. Schmid, Learning with hierarchical Gaussian kernels, 2016. preprint.pdf -
P. Thomann, I. Steinwart, I. Blaschzyk, and M. Meister, Spatial decompositions for large scale SVMs, 2016. preprint.pdf
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Emanuel Parzen, Extraction and Detection Problems and Reproducing Kernel Hilbert Spaces, 1962. Paper
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Hilbert Space Methods for Reduced-Rank Gaussian Process Regression. Arno Solin, Simo Sarkka. arxiv
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Operator-valued kernel-based vector autoregressive models for network inference. Néhémy Lim,Florence d’Alché-Buc,Cédric Auliac,George Michailidis.pdf
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End-to-End Kernel Learning with Supervised Convolutional Kernel Networks. Julien Mairal. pdf -
Information Rates of Nonparametric Gaussian Process Methods. Aad van der Vaart, Harry van Zanten; JMLR 12(Jun):2095−2119, 2011. pdf
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Supersamples from Kernel-Herding. Y. Chen, M. Welling and A. Smola. UAI 2010. pdf
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Randomized sketches for kernels: Fast and optimal non-parametric regression. Yun Yang, Mert Pilanci, Martin J. Wainwright. http://arxiv.org/abs/1501.06195
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Fast Randomized Kernel Methods With Statistical Guarantees. Ahmed El Alaoui, Michael W. Mahoney. http://arxiv.org/abs/1411.0306
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Kernels for Vector-Valued Functions: a Review. Mauricio A. Alvarez, Lorenzo Rosasco, Neil D. Lawrence. http://arxiv.org/abs/1106.6251
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Neal, R. M. (1994) ``Priors for infinite networks'', Technical Report CRG-TR-94-1, Dept. of Computer Science, University of Toronto. pdf