Linear matrix inequalities with chordal sparsity patterns and applications to robust quadratic optimization. - Martin S. Andersen 001; Lieven Vandenberghe; Joachim Dahl (CACSD, 2010)

Implementation of nonsymmetric interior-point methods for linear optimization over sparse matrix cones. - Martin S. Andersen 001; Joachim Dahl; Lieven Vandenberghe (Math. Program. Comput., 2010)

Distributed robust stability analysis of interconnected uncertain systems. - Martin S. Andersen 001; Anders Hansson; Sina Khoshfetrat Pakazad; Anders Rantzer (CDC, 2012)

Sparse multiple kernels for impulse response estimation with majorization minimization algorithms. - Tianshi Chen 001; Lennart Ljung; Martin S. Andersen 001; Alessandro Chiuso; Francesca Paola Carli; Gianluigi Pillonetto (CDC, 2012)

A convex relaxation of a dimension reduction problem using the nuclear norm. - Christian Lyzell; Martin S. Andersen 001; Martin Enqvist (CDC, 2012)

Logarithmic barriers for sparse matrix cones. - Martin S. Andersen 001; Joachim Dahl; Lieven Vandenberghe (Optim. Methods Softw., 2013)

Anomaly detection in homogenous populations: A sparse multiple kernel-based regularization method. - Tianshi Chen 001; Martin S. Andersen 001; Alessandro Chiuso; Gianluigi Pillonetto; Lennart Ljung (CDC, 2014)

Input-constrained model predictive control via the alternating direction method of multipliers. - Leo Emil Sokoler; Gianluca Frison; Martin S. Andersen 001; John Bagterp Jørgensen (ECC, 2014)

Generalized row-action methods for tomographic imaging. - Martin S. Andersen 001; Per Christian Hansen (Numer. Algorithms, 2014)

Decomposition in Conic Optimization with Partially Separable Structure. - Yifan Sun 001; Martin S. Andersen 001; Lieven Vandenberghe (SIAM J. Optim., 2014)

Robust Stability Analysis of Sparsely Interconnected Uncertain Systems. - Martin S. Andersen 001; Sina Khoshfetrat Pakazad; Anders Hansson; Anders Rantzer (IEEE Trans. Autom. Control., 2014)

System Identification Via Sparse Multiple Kernel-Based Regularization Using Sequential Convex Optimization Techniques. - Tianshi Chen 001; Martin S. Andersen 001; Lennart Ljung; Alessandro Chiuso; Gianluigi Pillonetto (IEEE Trans. Autom. Control., 2014)

Tomographic Image Reconstruction using Dictionary Priors. - Sara Soltani; Martin S. Andersen 001; Per Christian Hansen (CoRR, 2015)

Chordal Graphs and Semidefinite Optimization. - Lieven Vandenberghe; Martin S. Andersen 001 (Found. Trends Optim., 2015)

Distributed solutions for loosely coupled feasibility problems using proximal splitting methods. - Sina Khoshfetrat Pakazad; Martin S. Andersen 001; Anders Hansson (Optim. Methods Softw., 2015)

Tomographic image reconstruction using training images. - Sara Soltani; Martin S. Andersen 001; Per Christian Hansen (J. Comput. Appl. Math., 2017)

Inexact proximal Newton methods for self-concordant functions. - Jinchao Li; Martin S. Andersen 001; Lieven Vandenberghe (Math. Methods Oper. Res., 2017)

Distributed primal-dual interior-point methods for solving tree-structured coupled convex problems using message-passing. - Sina Khoshfetrat Pakazad; Anders Hansson; Martin S. Andersen 001; Isak Nielsen (Optim. Methods Softw., 2017)

Distributed Semidefinite Programming With Application to Large-Scale System Analysis. - Sina Khoshfetrat Pakazad; Anders Hansson; Martin S. Andersen 001; Anders Rantzer (IEEE Trans. Autom. Control., 2018)

A Convex Reconstruction Model for X-Ray Tomographic Imaging With Uncertain Flat-Fields. - Hari Om Aggrawal; Martin S. Andersen 001; Sean D. Rose; Emil Y. Sidky (IEEE Trans. Computational Imaging, 2018)

Spectral Computed Tomography with Linearization and Preconditioning. - Yunyi Hu; Martin S. Andersen 001; James G. Nagy (SIAM J. Sci. Comput., 2019)

An Image Registration Framework for Discontinuous Mappings Along Cracks. - Hari Om Aggrawal; Martin S. Andersen 001; Jan Modersitzki (WBIR, 2020)

Smoothing Splines and Rank Structured Matrices: Revisiting the Spline Kernel. - Martin S. Andersen 001; Tianshi Chen 001 (SIAM J. Matrix Anal. Appl., 2020)

On semiseparable kernels and efficient implementation for regularized system identification and function estimation. - Tianshi Chen 001; Martin S. Andersen 001 (Autom., 2021)

Regularization by Denoising Sub-sampled Newton Method for Spectral CT Multi-Material Decomposition. - Alessandro Perelli; Martin S. Andersen 001 (CoRR, 2021)

A Bayesian Approach to CT Reconstruction with Uncertain Geometry. - Frederik H. Pedersen; Jakob Sauer Jørgensen; Martin S. Andersen 001 (CoRR, 2022)

Low-rank flat-field correction for artifact reduction in spectral computed tomography. - Katrine O. Bangsgaard; Genoveva Burca; Evelina Ametova; Martin S. Andersen 001; Jakob Sauer Jørgensen (CoRR, 2022)

Towards Scalable Kernel-Based Regularized System Identification. - Lujing Chen; Tianshi Chen 001; Utkarsh Detha; Martin S. Andersen 001 (CDC, 2023)

An Efficient Implementation for Kernel-Based Regularized System Identification with Periodic Input Signals. - Zhuohua Shen; Yu Xu; Martin S. Andersen 001; Tianshi Chen 001 (CDC, 2023)

AdaSub: Stochastic Optimization Using Second-Order Information in Low-Dimensional Subspaces. - João Victor Galvão da Mata; Martin S. Andersen 001 (DSAA, 2023)

Link Prediction on Graphs Using NLP Embedding. - João Victor Galvão da Mata; Martin S. Andersen 001 (DSAA, 2023)

Preconditioner Design via the Bregman Divergence. - Andreas A. Bock; Martin S. Andersen 001 (CoRR, 2023)

A New Matrix Truncation Method for Improving Approximate Factorisation Preconditioners. - Andreas A. Bock; Martin S. Andersen 001 (CoRR, 2023)

Bayesian Inference with Projected Densities. - Jasper M. Everink; Yiqiu Dong; Martin S. Andersen 001 (SIAM/ASA J. Uncertain. Quantification, 2023)

Direct System Identification of Dynamical Networks with Partial Measurements: A Maximum Likelihood Approach. - João Victor Galvão da Mata; Anders Hansson; Martin S. Andersen 001 (ECC, 2024)

Sampling Strategies in Bayesian Inversion: A Study of RTO and Langevin Methods. - Remi Laumont; Yiqiu Dong; Martin S. Andersen 001 (CoRR, 2024)

Preconditioner Design via Bregman Divergences. - Andreas A. Bock; Martin S. Andersen 001 (SIAM J. Matrix Anal. Appl., 2024)

Connecting Kaporin's condition number and the Bregman log determinant divergence. - Andreas A. Bock; Martin S. Andersen 001 (CoRR, 2025)

A New Matrix Truncation Method for Improving Approximate Factorization Preconditioners. - Andreas A. Bock; Martin S. Andersen 001 (Numer. Linear Algebra Appl., 2025)

Identifiability and Maximum Likelihood Estimation for System Identification of Networks of Dynamical Systems. - Anders Hansson; João Victor Galvão da Mata; Martin S. Andersen 001 (CoRR, 2025)