225 citations · 752 across the 41 of their papers we have counts for
6 papers · 1 filter
Monte-Carlo Sampling Approach to Model Selection: A Primer
Petre Stoica, Xiaolei Shang, Yuanbo Cheng
Any data modeling exercise has two main components: parameter estimation and model selection. The latter will be the topic of this lecture note. More concretely we will introduce s…
The Cramer-Rao Bound for Signal Parameter Estimation from Quantized Data
Petre Stoica, Xiaolei Shang, Yuanbo Cheng
Several current ultra-wide band applications, such as millimeter wave radar and communication systems, require high sampling rates and therefore expensive and energy-hungry analogt…
MIMO Multifunction RF Systems: Detection Performance and Waveform Design
Bo Tang, Petre Stoica
This paper studies the detection performance of a multiple-input-multiple-output (MIMO) multifunction radio frequency (MFRF) system, which simultaneously supports radar, communicat…
Diagnostic Tool for Out-of-Sample Model Evaluation
Ludvig Hult, Dave Zachariah, Petre Stoica
Assessment of model fitness is a key part of machine learning. The standard paradigm is to learn models by minimizing a chosen loss function averaged over training data, with the a…
Learning Sparse Graphs via Majorization-Minimization for Smooth Node Signals
Ghania Fatima, Aakash Arora, Prabhu Babu +1
In this letter, we propose an algorithm for learning a sparse weighted graph by estimating its adjacency matrix under the assumption that the observed signals vary smoothly over th…
Tuned Regularized Estimators for Linear Regression via Covariance Fitting
Per Mattsson, Dave Zachariah, Petre Stoica
We consider the problem of finding tuned regularized parameter estimators for linear models. We start by showing that three known optimal linear estimators belong to a wider class…