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05/11/2023
Two new algorithms for maximum likelihood estimation of sparse covariance matrices with applications to graphical modeling
In this paper, we propose two new algorithms for maximum-likelihood esti...
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05/10/2023
Pearson-Matthews correlation coefficients for binary and multinary classification and hypothesis testing
The Pearson-Matthews correlation coefficient (usually abbreviated MCC) i...
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05/10/2023
Fair principal component analysis (PCA): minorization-maximization algorithms for Fair PCA, Fair Robust PCA and Fair Sparse PCA
In this paper we propose a new iterative algorithm to solve the fair PCA...
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04/18/2023
Low-rank covariance matrix estimation for factor analysis in anisotropic noise: application to array processing and portfolio selection
Factor analysis (FA) or principal component analysis (PCA) models the co...
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09/27/2022
Monte-Carlo Sampling Approach to Model Selection: A Primer
Any data modeling exercise has two main components: parameter estimation...
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08/25/2022
MIMO Multifunction RF Systems: Detection Performance and Waveform Design
This paper studies the detection performance of a multiple-input-multipl...
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06/22/2022
Diagnostic Tool for Out-of-Sample Model Evaluation
Assessment of model fitness is an important step in many problems. Model...
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02/06/2022
Learning Sparse Graphs via Majorization-Minimization for Smooth Node Signals
In this letter, we propose an algorithm for learning a sparse weighted g...
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01/21/2022
Tuned Regularized Estimators for Linear Regression via Covariance Fitting
We consider the problem of finding tuned regularized parameter estimator...
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10/19/2021
Learning Pareto-Efficient Decisions with Confidence
The paper considers the problem of multi-objective decision support when...
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05/18/2021
Distributionally Robust Learning in Heterogeneous Contexts
We consider the problem of learning from training data obtained in diffe...
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10/09/2020
Robust Localization in Wireless Networks From Corrupted Signals
We address the problem of timing-based localization in wireless networks...
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07/03/2020
Prediction of Spatial Point Processes: Regularized Method with Out-of-Sample Guarantees
A spatial point process can be characterized by an intensity function wh...
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12/16/2019
Robust Prediction when Features are Missing
Predictors are learned using past training data containing features whic...
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08/01/2019
Max-Min Fairness Design for MIMO Interference Channels: a Minorization-Maximization Approach
We address the problem of linear precoder (beamformer) design in a multi...
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02/26/2019
Effect Inference from Two-Group Data with Sampling Bias
In many applications, different populations are compared using data that...
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08/17/2018
Data Consistency Approach to Model Validation
In scientific inference problems, the underlying statistical modeling as...
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05/19/2017
Model-Robust Counterfactual Prediction Method
We develop a method for assessing counterfactual predictions with multip...
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03/15/2017
Online Learning for Distribution-Free Prediction
We develop an online learning method for prediction, which is important ...
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06/14/2016
Recursive nonlinear-system identification using latent variables
In this paper we develop a method for learning nonlinear systems with mu...
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06/13/2016