53 citations · 143 across the 24 of their papers we have counts for
5 papers · 1 filter
Generalized system identification with stable spline kernels
Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto
Regularized least-squares approaches have been successfully applied to linear system identification. Recent approaches use quadratic penalty terms on the unknown impulse response d…
Linear system identification using stable spline kernels and PLQ penalties
Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto
The classical approach to linear system identification is given by parametric Prediction Error Methods (PEM). In this context, model complexity is often unknown so that a model ord…
Convex vs nonconvex approaches for sparse estimation: GLasso, Multiple Kernel Learning and Hyperparameter GLasso
Aleksandr Y. Aravkin, James V. Burke, Alessandro Chiuso +1
The popular Lasso approach for sparse estimation can be derived via marginalization of a joint density associated with a particular stochastic model. A different marginalization of…
The connection between Bayesian estimation of a Gaussian random field and RKHS
Aleksandr Y. Aravkin, Bradley M. Bell, James V. Burke +1
Reconstruction of a function from noisy data is often formulated as a regularized optimization problem over an infinite-dimensional reproducing kernel Hilbert space (RKHS). The sol…
Sparse/Robust Estimation and Kalman Smoothing with Nonsmooth Log-Concave Densities: Modeling, Computation, and Theory
Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto
We introduce a class of quadratic support (QS) functions, many of which play a crucial role in a variety of applications, including machine learning, robust statistical inference,…