Linear Mixed-Effects (LME) models are a fundamental tool for modeling
co...
Compressed sensing is a central topic in signal processing with myriad
a...
State-space models are used in a wide range of time series analysis
form...
Generalized matrix-fractional (GMF) functions are a class of matrix supp...
Regularized least-squares approaches have been successfully applied to l...
We present a Kalman smoothing framework based on modeling errors using t...
The classical approach to linear system identification is given by param...
In this paper, we present the optimization formulation of the Kalman
fil...
The popular Lasso approach for sparse estimation can be derived via
marg...
Reconstruction of a function from noisy data is often formulated as a
re...
We introduce a class of quadratic support (QS) functions, many of which ...
Kalman filtering and smoothing algorithms are used in many areas, includ...