F. P. Carli, "On the maximum entropy property of the first-order stable spline kernel and its implications," in Proc. IEEE Multi-Conf. Systems Control, 2014, pp. 409-414.
F. P. Carli, T. Chen, A. Chiuso, L. Ljung, and G. Pillonetto, "On the estimation of hyperparameters for bayesian system identification with exponentially decaying kernels," in Proc. IEEE CDC, 2012, pp. 5260-5265.
F. P. Carli, A. Chiuso, and G. Pillonetto, "Efficient algorithms for large scale linear system identification using stable spline estimators," in Proc. IFAC SysId, 2012, pp. 119-124.
T. Chen and L. Ljung "Implementation of algorithms for tuning parameters in regularized least squares problems in system identification," Automatica, vol. 49, no. 7, 2013, pp. 2213-2220.
T. Chen, H. Ohlsson, and L. Ljung, "On the estimation of transfer functions, regularizations and Gaussian processes-revisited," Automatica, vol. 48, no. 8, pp. 1525-1535, 2012.
J. Dahl, L. Vanderberghe, and V. Roychowdhury, "Covariance selection for non-chordal graphs via chordal embedding," Optimiz. Methods Softw., vol. 23, pp. 501-520, 2008.
A. Dempster, "Covariance selection," Biometrics, vol. 28, pp. 157-175, 1972.
H. Dym and I. Gohberg, "Extensions of band matrices with band inverses," Linear Algebra Its Appl., vol. 36, pp. 1-24, 1981.
I. Gohberg, S. Goldberg, and M. A. Kaashoek, Classes of Linear Operators, II, OT63. Birkhäuser, Basel, Switzerland, 1993.
G. H. Golub and C. F. Van Loan, Matrix Computations. Baltimore, MD, USA: Johns Hopkins Univ. Press, 1996.
R. Grone, C. R. Johnson, E. M. Sa, and H. Wolkowicz, "Positive definite completions of partial Hermitian matrices," Linear Algebra Its Appl., vol. 58, pp. 109-124, 1984.
R. Hunger, "Floating point operations in matrix-vector calculus," Tech. Rep., Munich Univ. Technol. Munich, Germany, 2007.
C. R. Johnson, "Matrix completion problems: a survey," in Proc. Symposia in Applied Mathematics, 1990, vol. 40, pp. 171-198.
S. L. Lauritzen, Graphical Models. Oxford, U.K.: Oxford Univ. Press 1996.
J. S. Maritz and T. Lwin, Empirical Bayes Methods. London, U.K.: Chapman and Hall, 1989.
G. Pillonetto and G. De Nicolao, "A new kernel-based approach for linear system identification," Automatica, vol. 46, pp. 81-93, 2010.
G. Pillonetto and G. De Nicolao, "Kernel selection in linear system identification Part I: A Gaussian process perspective," in Proc. IEEE CDCECC, 2011, pp. 4318-4325.
G. Pillonetto, F. Dinuzzo, T. Chen, G. De Nicolao, and L. Ljung, "Kernel methods in system identification, machine learning and function estimation: A survey," Automatica, vol. 50, no. 3, pp. 657-682, 2014.
C. Rasmussen and C. Williams, Gaussian Processes for Machine Learning. Cambridge, MA, USA: MIT Press, 2006.
J. Shawe-Taylor and N. Cristianini, Kernel Methods for Pattern Analysis. Cambridge, U.K.: Cambridge Univ. Press, 2004.
R. Tibshirani, "Regression shrinkage and selection via the lasso," J. Roy. Statist. Soc., ser. B, Methodological, vol. 58, no. 1, pp. 267-288, 1996.
A. N. Tikhonov and V. Arsenin, Solutions of Ill-Posed Problems. Winston, Great Falls, MT, 1977.
