Reproducing Kernel Hilbert Spaces in Probability and Statistics, 2011. ,
DOI : 10.1007/978-1-4419-9096-9
Near-Optimal Column-Based Matrix Reconstruction, SIAM Journal on Computing, vol.43, issue.2, pp.687-717, 2014. ,
DOI : 10.1137/12086755X
URL : http://arxiv.org/abs/1103.0995
A walk through energy, discrepancy, numerical integration and group invariant measures on measurable subsets of euclidean space, Numerical Algorithms, vol.74, issue.1, pp.213-235, 2008. ,
DOI : 10.1007/s11075-008-9187-6
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, issue.1, pp.805-825, 2014. ,
DOI : 10.1137/130928534
URL : https://hal.archives-ouvertes.fr/hal-00913466
Convex relaxation for IMSE optimal design in random-field models, Computational Statistics & Data Analysis, 2016. ,
DOI : 10.1016/j.csda.2016.10.018
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, pp.110-119, 1986. ,
DOI : 10.1007/BF01589445
Integral Equations: Theory and Numerical Treatment, Birkhäuser, vol.120, pp.2012-2038 ,
DOI : 10.1007/978-3-0348-9215-5
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. ,
Random Number Generation and Quasi-Monte Carlo Methods, 1992. ,
DOI : 10.1137/1.9781611970081
A new approach to variable selection in least squares problems, IMA journal of numerical analysis, vol.20, issue.3, pp.389-403, 2000. ,
L1-regularization path algorithm for generalized linear models, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.69, issue.4, pp.659-677, 2007. ,
Design of Experiments in Nonlinear Models, 2013. ,
DOI : 10.1007/978-1-4614-6363-4
URL : https://hal.archives-ouvertes.fr/hal-00879984
Estimating the Support of a High-Dimensional Distribution, Neural Computation, vol.6, issue.1, pp.1443-1471, 2001. ,
DOI : 10.1214/aos/1069362732
Karhunen???Lo??ve approximation of random fields by generalized fast multipole methods, Journal of Computational Physics, vol.217, issue.1, pp.100-122, 2006. ,
DOI : 10.1016/j.jcp.2006.01.048
Analyse Hilbertienne. Hermann, 1978. ,
Geometry on probability spaces. Constructive Approximation, pp.311-323, 2009. ,
DOI : 10.1007/s00365-009-9070-2
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. ,