F. Bach, 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

F. Bach, S. Lacoste-julien, and G. Obozinski, On the Equivalence between Herding and Conditional Gradient Algorithms, International Conference on Machine Learning (ICML), 2012.
URL : https://hal.archives-ouvertes.fr/hal-00681128

R. Bardenet and A. Hardy, Monte Carlo with Determinantal Point Processes, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01311263

F. Briol, C. J. Oates, M. Girolami, M. A. Osborne, and . Frank-wolfe-bayesian-quadrature, Probabilistic Integration with Theoretical Guarantees, Advances in Neural Information Processing Systems (NeurIPS), pp.1162-1170, 2015.

Y. Chen, M. Welling, and A. Smola, Super-Samples from Kernel Herding, Conference on Uncertainty in Artificial Intelligence (UAI), pp.109-116, 2010.

Y. Chow, L. Gatteschi, and R. Wong, A Bernstein-type inequality for the Jacobi polynomial, Proceedings of the American Mathematical Society, vol.121, issue.3, pp.703-703, 1994.

P. J. Davis and P. Rabinowitz, Methods of numerical integration, vol.9780122063602, 1984.

B. Delyon and F. Portier, Integral approximation by kernel smoothing, Bernoulli, vol.22, issue.4, pp.2177-2208, 2016.
DOI : 10.3150/15-bej725
URL : https://hal.archives-ouvertes.fr/hal-01321471

M. Derezínski, Fast determinantal point processes via distortion-free intermediate sampling, 2019.

J. Dick and F. Pillichshammer, Digital nets and sequences : discrepancy and quasi-Monte Carlo integration, vol.9780521191593, 2010.
DOI : 10.1007/978-3-319-04696-9_9

S. M. Ermakov and V. G. Zolotukhin, Polynomial Approximations and the Monte-Carlo Method, Theory of Probability & Its Applications, vol.5, issue.4, pp.428-431, 1960.
DOI : 10.1137/1105046

M. Evans and T. Swartz, Approximating integrals via Monte Carlo and deterministic methods, vol.9780198502784, 2000.

G. Gautier, R. Bardenet, M. Valko, and . Dppy, Sampling Determinantal Point Processes with Python. ArXiv eprints, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01879424

W. Gautschi, How sharp is Bernstein's Inequality for Jacobi polynomials?, Electronic Transactions on Numerical Analysis, vol.36, pp.1-8, 2009.

J. B. Hough, M. Krishnapur, Y. Peres, and B. Virág, Determinantal Processes and Independence, The Institute of Mathematical Statistics and the Bernoulli Society, vol.3, pp.206-229, 2006.
DOI : 10.1214/154957806000000078
URL : https://doi.org/10.1214/154957806000000078