On the equivalence between kernel quadrature rules and random feature expansions, Journal of Machine Learning Research, vol.18, issue.21, pp.1-38, 2017. ,
URL : https://hal.archives-ouvertes.fr/hal-01118276
, Generalized Inverses: Theory and Applications, 2003.
Reproducing Kernel Hilbert Spaces in Probability and Statistics, 2011. ,
Near-optimal column-based matrix reconstruction, SIAM Journal on Computing, vol.43, issue.2, pp.687-717, 2014. ,
A walk through energy, discrepancy, numerical integration and group invariant measures on measurable subsets of Euclidean space, Numerical Algorithms, vol.48, issue.1-3, pp.213-235, 2008. ,
On energy, discrepancy and group invariant measures on measurable subsets of Euclidean space, Journal of Fourier Analysis and Applications, vol.16, issue.6, pp.813-839, 2010. ,
On the Nyström method for approximating a Gram matrix for improved kernel-based learning, Journal of Machine Learning Research, vol.6, pp.2153-2175, 2005. ,
Spectral approximation of the IMSE criterion for optimal designs in kernel-based interpolation models, SIAM/ASA Journal on Uncertainty Quantification, vol.2, pp.805-825, 2014. ,
URL : https://hal.archives-ouvertes.fr/hal-00913466
Convex relaxation for IMSE optimal design in random-field models, Computational Statistics and Data Analysis, vol.113, pp.375-394, 2017. ,
URL : https://hal.archives-ouvertes.fr/hal-01246483
Revisiting the Nyström method for improved large-scale machine learning, Journal of Machine Learning Research, vol.17, pp.1-65, 2016. ,
Some comments on Wolfe's "away step, Mathematical Programming, vol.35, pp.110-119, 1986. ,
The entire regularization path for the Support Vector Machine, Journal of Machine Learning Research, vol.5, pp.1391-1415, 2004. ,
Statistical Learning with Sparsity: the Lasso and Generalizations, 2015. ,
Sampling methods for the Nyström method, Journal of Machine Learning Research, vol.13, pp.981-1006, 2012. ,
UCI Machine Learning Repository, 2013. ,
Random Number Generation and Quasi, 1992. ,
A new approach to variable selection in least squares problems, IMA journal of numerical analysis, vol.20, issue.3, pp.389-403, 2000. ,
Design of Experiments in Nonlinear Models, 2013. ,
URL : https://hal.archives-ouvertes.fr/hal-00879984
Estimating the support of a high-dimensional distribution, Neural Computation, vol.13, issue.7, pp.1443-1471, 2001. ,
Equivalence of distance-based and RKHS-based statistics in hypothesis testing, The Annals of Statistics, pp.2263-2291, 2013. ,
Learning theory estimates via integral operators and their approximations. Constructive Approximation, vol.26, pp.153-172, 2007. ,
Geometry on probability spaces. Constructive Approximation, vol.30, pp.311-323, 2009. ,
Support Vector Machines, 2008. ,
Improving CUR matrix decomposition and the Nyström approximation via adaptive sampling, Journal of Machine Learning Research, vol.14, pp.2729-2769, 2013. ,
Clustered Nyström method for large scale manifold learning and dimension reduction, IEEE Transactions on Neural Networks, vol.21, issue.10, pp.1576-1587, 2010. ,
Reproducing Kernel Hilbert Spaces in Probability and Statistics, 2004. ,
Optimal quadrature-sparsification for integral operator approximation, SIAM Journal on Scientific Computing, vol.40, issue.5, pp.3636-3674, 2018. ,
URL : https://hal.archives-ouvertes.fr/hal-01416786