Cristian R. Rojas
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Journal Papers

  1. C. R. Rojas, R. A. Rojas, and M. E. Salgado. “Equivalence between transfer-matrix and observed-state feedback control”. IEE Proceedings on Control Theory and Applications (Part D), 153(2): 147-155, 2006. [link]

  2. C. R. Rojas, J. S. Welsh, G. C. Goodwin, and A. Feuer. “Robust optimal experiment design for system identification”. Automatica, 43(6): 993-1008, 2007. [pdf|link]

  3. G. C. Goodwin, J. C. Agüero, J. S. Welsh, J. I. Yuz, G. J. Adams, and C. R. Rojas. “Robust identification of process models from plant data”. Journal of Process Control, 18(9): 810-820, 2008. [pdf|link]

  4. C. R. Rojas, J. C. Agüero, J. S. Welsh, and G. C. Goodwin. “On the equivalence of least costly and traditional experiment design for control”. Automatica, 44(11): 2706-2715, 2008. [pdf|link]

  5. C. R. Rojas, J. S. Welsh, and J. C. Agüero. “Fundamental limitations on the variance of estimated parametric models”. IEEE Transactions on Automatic Control, 54(5): 1077-1081, 2009. [pdf|link]

  6. C. R. Rojas, M. Barenthin, J. S. Welsh, and H. Hjalmarsson. “The cost of complexity in system identification: Frequency function estimation of Finite Impulse Response systems”. IEEE Transactions on Automatic Control, 55(10):2298-2309, 2010. [link]

  7. J. A. Ramírez, C. R. Rojas, J. C. Jarur, and R. A. Rojas. “Aportes a la teoría y la implementación del método LSCR”. Revista Iberoamericana de Automática e Informática Industrial (RIAI), 7(3):83-94, 2010 (in spanish). [link]

  8. J. Mårtensson, C. R. Rojas, and H. Hjalmarsson. “Conditions when minimum variance control is the optimal experiment for identifying a minimum variance control”. Automatica, 47(3):578-583, 2011. [link]

  9. A. Esparza, J. C. Agüero, C. R. Rojas and B. I. Godoy. “Asymptotic statistical analysis of some controller design strategies”. Automatica, 47(5):1041-1046, 2011. [link]

  10. C. R. Rojas, H. Hjalmarsson, L. Gerencsér, and J. Mårtensson. “An adaptive method for consistent estimation of real-valued non-minimum phase zeros in stable LTI systems”. Automatica, 47(7):1388-1398, 2011. [link]

  11. K. E. J. Olofsson, P. R. Brunsell, C. R. Rojas, J. R. Drake, and H. Hjalmarsson. “Predictor-based multivariable closed-loop system identification of the EXTRAP T2R reversed field pinch external plasma response”. Plasma Physics and Controlled Fusion, 53(8), 2011. [link]

  12. C. R. Rojas, M. Barenthin, J. S. Welsh, and H. Hjalmarsson. “The cost of complexity in system identification: The Output Error case”. Automatica, 47(9):1938-1948, 2011. [link]

  13. C. R. Rojas, P. Zetterberg, and P. Händel. “Transceiver inphase/quadrature imbalance, ellipse fitting, and the universal software radio peripheral”. IEEE Transactions on Instrumentation and Measurement, 60(11):3629-3639, 2011. [pdf|link]

  14. H. Hjalmarsson, J. Mårtensson, C. R. Rojas and T. Södeström. “On the accuracy in errors-in-variables identification compared to prediction-error identification”. Automatica, 47(12):2704-2712, 2011. [link]

  15. C. Mueller, C. R. Rojas, and G. C. Goodwin. “Generation of amplitude constrained signals with a prescribed spectrum”. Automatica, 48(1):153-158, 2012. [pdf|link]

  16. J. C. Agüero, C. R. Rojas, H. Hjalmarsson, and G. C. Goodwin. “Accuracy of linear multiple-input multiple-output (MIMO) models obtained by maximum likelihood estimation”. Automatica, 49(4):632-637, 2012. [link]

  17. C. R. Rojas, J. C. Agüero, J. S. Welsh, G. C. Goodwin, and A. Feuer. “Robustness in experiment design”. IEEE Transactions on Automatic Control, 57(4):860-874, 2012. [pdf|link]

  18. B. Sanchez, C. R. Rojas, G. Vandersteen, R. Bragos, and J. Schoukens. “On the calculation of the D-optimal power spectrum for impedance spectroscopy measurements”. Measurement Science and Technology, 23(8):085702, 2012. [link]

  19. C. R. Rojas, T. Oomen, H. Hjalmarsson, and B. Wahlberg. “Analyzing iterations in identification with application to nonparametric \(\mathcal{H}_\infty\)-norm estimation”. Automatica, 48(11):2776-2790, 2012. [pdf|link]

  20. H. Hjalmarsson, C. R. Rojas, and D. E. Rivera. “System identification: A Wiener-Hammerstein benchmark”. Control Engineering Practice, 20(11):1095–1096, 2012.

  21. D. Katselis, C. R. Rojas, M. Bengtsson, and H. Hjalmarsson. “Frequency smoothing gains in preamble-based channel estimation for multicarrier systems”. Signal Processing, 93(9):2777-2782, 2013. [link]

  22. C. R. Rojas, D. Katselis, and H. Hjalmarsson. “A note on the SPICE method”. IEEE Transactions on Signal Processing, 61(18):4545-4551, 2013. [pdf|link|arxiv]

  23. D. Eckhard, A. S. Bazanella, C. R. Rojas, and H. Hjalmarsson. “Input design as a tool to improve the convergence of PEM”. Automatica, 49(11):3282-3291, 2013. [link]

  24. D. Katselis, C. R. Rojas, M. Bengtsson, E. Björnson, X. Bombois, N. Shariati, M. Jansson, and H. Hjalmarsson. “Training sequence design for MIMO channels: An application-oriented approach”. EURASIP Journal on Wireless Communications and Networking, 2013:245, 2013. [link]

  25. B. Sanchez and C. R. Rojas. “Robust excitation power spectrum design for broadband impedance spectroscopy”. Measurement Science and Technology, 25(6):065501, 2014. [link]

  26. T. Oomen, R. van der Maas, C. R. Rojas, and H. Hjalmarsson. “Iterative data-driven \(\mathcal{H}_\infty\)-norm estimation of multivariable systems with application to robust active vibration isolation”. IEEE Transactions on Control Systems Technology, 22(6):2247-2260, 2014. [link]

  27. C. R. Rojas, R. Tóth, and H. Hjalmarsson. “Sparse estimation of polynomial and rational dynamical models”. IEEE Transactions on Automatic Control, 59(11):2962-2977, 2014. [link]

  28. V. Krishnamurthy and C. R. Rojas. “Reduced complexity filtering with stochastic dominance bounds: A convex optimization approach”. IEEE Transactions on Signal Processing, 62(23):6309-6322, 2014. [arxiv]

  29. D. Katselis and C. R. Rojas. “Application-oriented estimator selection”. IEEE Signal Processing Letters, 22(4):489-493, 2015.

  30. P. E. Valenzuela, C. R. Rojas, and H. Hjalmarsson. “A graph theoretical approach to input design for identification of nonlinear dynamical models”. Automatica, 51(1):233-242, 2015.

  31. D. Katselis, C. R. Rojas, B. I. Godoy, J. C. Agüero, and C. L. Beck. “On the end-performance metric estimator selection”. Automatica, 58:22-27, 2015.

  32. N. Blomberg, C. R. Rojas, and B. Wahlberg. “Regularization paths for re-weighted nuclear norm minimization”. IEEE Signal Processing Letters, 22(11):1980–1984, 2015.

  33. C. A. Larsson, C. R. Rojas, X. Bombois, and H. Hjalmarsson. “Experimental eval- uation of model predictive control with excitation (MPC-X) on an industrial de- propanizer”. Journal of Process Control, 31:1–16, 2015.

  34. M. Malek-Mohammadi, C. R. Rojas, M. Jansson, and M. Babaie-Zadeh. “Upper bounds on the error of sparse vector and low-rank matrix recovery”. Signal Processing, 120:249–254, 2016.

  35. J. Ottersten, B. Wahlberg, and C. R. Rojas. “Accurate changing point detection for l1 mean filtering”. IEEE Signal Processing Letters, 23(2):297–301, 2016.

  36. K. Li, M. Sundin, C. R. Rojas, S. Chatterjee, and M. Jansson. “Alternating strategies with internal ADMM for low-rank matrix reconstruction”. Signal Processing, 121:153–159, 2016.

  37. M. Sundin, C. R. Rojas, M. Jansson, and S. Chatterjee. “Relevance Singular Vector Machine for Low-rank Matrix Reconstruction”. IEEE Transactions on Signal Processing, 64(20):5327–5339, 2016. [arxiv]

  38. M. Malek-Mohammadi, A. Koochakzadeh, M. Babaie-Zadeh, M. Jansson, and C. R. Rojas. “Successive concave sparsity approximation for compressed sensing”. IEEE Transactions on Signal Processing, 64(21):5657–5671, 2016.

  39. M. Malek-Mohammadi, C. R. Rojas, and B. Wahlberg. “A class of nonconvex penalties preserving overall convexity in optimization-based mean filtering”. IEEE Transactions on Signal Processing, 64(24):6650–6664, 2016.

  40. C. A. Larsson, A. Ebadat, C. R. Rojas, X. Bombois, and H. Hjalmarsson. “An application-oriented approach to dual control with excitation for closed-loop identification”. European Journal of Control, 29:1-16, 2016.

  41. L. Özkan, X. Bombois, J. H. A. Ludlage, C. R. Rojas, H. Hjalmarsson, P. E. Modén, M. Lundh, T. C. P. M. Backx, and P. M. J. Van den Hof. “Advanced autonomous model-based operation of industrial process systems (Autoprofit): Technological developments and future perspectives”. Annual Reviews in Control, 42:126-142, 2016.

  42. D. Eckhard, A. Bazanella, C. R. Rojas and H. Hjalmarsson. “Cost function shaping of the output error criterion”. Automatica, 76:53-60, 2017.

  43. P. E. Valenzuela, J. Dahlin, C. R. Rojas, and T. B. Schön. “On robust input design for nonlinear dynamical models”. Automatica, 77:268-278, 2017.

  44. N. Everitt, G. Bottegal, C. R. Rojas, and H. Hjalmarsson. “Variance analysis of linear SIMO models with spatially correlated noise”. Automatica, 77:68-81, 2017. [arxiv]

  45. A. Ebadat, P. E. Valenzuela, C. R. Rojas, and B. Wahlberg. “Model predictive control oriented experiment design for system identification: A graph theoretical approach”. Journal of Process Control, 52:75-84, 2017.

  46. R. A. González, P. E. Valenzuela, C. R. Rojas, and R. A. Rojas. “Optimal enforcement of causality in non-parametric transfer function estimation”. IEEE Control Systems Society Letters, 1(2):268-273, 2017. [pdf]

  47. T. Oomen and C. R. Rojas. “Sparse iterative learning control with application to a wafer stage: Achieving performance, resource efficiency, and task flexibility”. IFAC Mechatronics, 47:134-147, 2017. [arxiv]

  48. R. Mattila, C. R. Rojas, V. Krishnamurthy, and B. Wahlberg. “Asymptotically efficient identification of known-sensor hidden Markov models”. IEEE Signal Processing Letters, 24(12):1813-1817, 2017. [arxiv]

  49. J. Bjurgert, P. E. Valenzuela, and C. R. Rojas. “On adaptive boosting for system identification”. IEEE Transactions on Neural Networks and Learning Systems, 29(9):4510-4514, 2018.

  50. P. E. Valenzuela, T. B. Schön, and C. R. Rojas. “On model order priors for Bayesian identification of SISO linear systems”. International Journal of Control, 1-17, 2017.

  51. H. Ha, J. S. Welsh, C. R. Rojas, and B. Wahlberg. “An analysis of the SPARSEVA estimate for the finite sample data case”. Automatica, 96:141-149, 2018.

  52. P. E. Valenzuela, C. R. Rojas, and H. Hjalmarsson. “Analysis of averages over distributions of Markov processes”. Automatica, 98:354-357, 2018.

  53. M. Galrinho, C. R. Rojas, and H. Hjalmarsson. “Parametric identification using weighted null-space fitting”. IEEE Transactions on Automatic Control, 64(7):2798-2813,2018. [arxiv]

  54. M. Galrinho, C. R. Rojas, and H. Hjalmarsson. “Estimating models with high-order noise dynamics using semi-parametric weighted null-space fitting”. Automatica, 102:45-57, 2019. [arxiv]

  55. R. Mattila, I. Lourenço, C. R. Rojas, V. Krishnamurthy, and B. Wahlberg. “Estimating private beliefs of Bayesian agents based on observed decisions”. IEEE Control Systems Letters, 3(3):523-528, 2019.

  56. H. Kwon, C. R. Rojas, S. Rutkove, and B. Sanchez. “Three-harmonic optimal multi-sine input power spectrum for bioimpedance identification”. Physiological Measurement, 40(5):05NT02, 2019.

  57. S. Pan, R. A. González, J. Welsh, and C. R. Rojas. “Consistency analysis of the simplified refined instrumental variable method for continuous-time systems”. Automatica, 113:108767, 2020. [arxiv]

  58. S. Pan, J. Welsh, R. A. González, and C. R. Rojas. “Efficiency analysis of the simplified refined instrumental variable method for continuous-time systems”. Automatica, 121:109196, 2020. [arxiv]

  59. R. Mattila, C. R. Rojas, V. Krishnamurthy, and B. Wahlberg. “Inverse filtering for hidden Markov models with applications to counter-adversarial autonomous systems”. IEEE Transactions on Signal Processing, 68:4987–5002, 2020. [arxiv]

  60. B. Djehiche, O. Mazhar, and C. R. Rojas. “Finite impulse response models: A non-asymptotic analysis of the least squares estimator”. Bernoulli, 27(2):976–1000, 2021.

  61. R. A. González, C. R. Rojas, S. Pan, and J. Welsh. “Consistent identification of continuous-time systems under multisine input signal excitation”. Automatica, 133:109859, 2021. [arxiv]

  62. I. Lourenço, R. Mattila, C. R. Rojas, X. Hu, and B. Wahlberg. “Hidden Markov models: Inverse filtering, belief estimation and privacy protection”. Journal of Systems Science and Complexity, 34:1801-1820, 2021.

  63. M. I. Müller and C. R. Rojas. “Risk-theoretic optimal design of output-feedback controllers via iterative convex relaxations”. Automatica, 136:110042, 2022.

  64. R. A. González, C. R. Rojas, S. Pan, and J. Welsh. “Theoretical and practical aspects of the convergence of the SRIVC estimator for over-parameterized models”. Automatica, 142:110355, 2022.

  65. R. Mochaourab, I. Samsten, A. Venkitaraman, P. Papapetrou, and C. R. Rojas. “Interpretable time series classification: A signal processing perspective”. IEEE Signal Processing Magazine, 39(4):119-129, 2022.

  66. J. Parsa, C. R. Rojas, and H. Hjalmarsson. “Application-oriented input design with low coherence constraint”. IEEE Control Systems Letters, 7:193-198, 2022.

  67. S. Pan, J. Welsh, R. A. González, and C. R. Rojas. “Consistency analysis and bias elimination of the instrumental variable based state variable filter method”. Automatica, 144:110511, 2022.

  68. P. Wachel and C. R. Rojas. “An adversarial approach to adaptive model predictive control”. Journal of Advances in Applied & Computational Mathematics, 9, 135-146, 2022. [link]

  69. C. R. Rojas and P. Wachel. “On state-space representations of general discrete-time dynamical systems”. IEEE Transactions on Automatic Control, 67(12):6975–6979, 2022. [arxiv]

  70. R. A. González, C. R. Rojas, S. Pan, and J. S. Welsh. “On the relation between discrete and continuous-time refined instrumental variable methods”. IEEE Control Systems Letters, 7:2233–2238, 2023. [arxiv]

  71. R. A. González, C. R. Rojas, S. Pan, and J. S. Welsh. ’'Refined instrumental variable methods for unstable continuous-time systems in closed-loop’’. International Journal of Control, 96(10):2527-2541, 2023. [pdf]

  72. J. Parsa, C. R. Rojas, S. Pan, and H. Hjalmarsson. “Coherence-based input design for nonlinear systems”. IEEE Control Systems Letters, 7:2934-2939, 2023.

  73. P. Wachel, K. Kowalczyk and C. R. Rojas. “Decentralized diffusion-based learning under non-parametric limited prior knowledge”. European Journal of Control, 75:100912, 2024.

  74. T. Oomen and C. R. Rojas. “Reset-free data-driven gain estimation: Power iteration using reversed-circulant matrices”. Automatica, 161:111505, 2024.

  75. J. Parsa, C. R. Rojas, and H. Hjalmarsson. “Transformation of regressors for low coherent sparse system identification”. IEEE Transactions on Automatic Control (accepted for publication), 2023.

  76. R. A. González, S. Pan, C. R. Rojas, and J. S. Welsh. “Consistency analysis of refined instrumental variable methods for continuous-time system identification in closed-loop”. Automatica (accepted for publication), 2024.

  77. R. A. González, K. Classens, C. R. Rojas, J. Welsh, and T. Oomen. “Statistical analysis of block coordinate descent algorithms for linear continuous-time system identification”, IEEE Control Systems Letters (accepted for publication), 2024.

Conference Papers

  1. R. A. Rojas and C. R. Rojas. “The inverse of sampling revisited”. In Proceedings of the IASTED Conference on Intelligent Systems and Control (ISC-2001), 2001.

  2. J. S. Welsh and C. R. Rojas. “Frequency localising basis functions for wide-band system identification: A condition number bound for output error systems”. In Proceedings of the European Control Conference (ECC), pages 4618-4624, Kos, Greece, July 2007. [pdf]

  3. C. R. Rojas, G. C. Goodwin, J. S. Welsh, and A. Feuer. “Optimal experiment design with diffuse prior information”. In Proceedings of the European Control Conference (ECC), pages 935-940, Kos, Greece, July 2007. [pdf]

  4. C. R. Rojas, J. S. Welsh, and G. C. Goodwin. “A receding horizon algorithm to generate binary signals with a prescribed autocovariance”. In Proceedings of the 2007 American Control Conference (ACC), pages 122-127, New York, July 2007. [pdf|link]

  5. G. C. Goodwin, J. C. Agüero, J. S. Welsh, G. J. Adams, J. I. Yuz, and C. R. Rojas. “Robust identification of process models from plant data”. In Proceedings of the 8th IFAC Symposium on Dynamics and Control of Process Systems (DYCOPS), pages 1-18, Cancún, Mexico, 2007. [pdf]

  6. J. S. Welsh, C. R. Rojas, and S. D. Mitchell. “Wideband parametric identification of a power transformer”. In Proceedings of the Australian Universities Power Engineering Conference (AUPEC), Perth, Australia, December 2007. [pdf|link]

  7. C. R. Rojas, M. Barenthin, J. S. Welsh, and H. Hjalmarsson. “The cost of complexity in identification of FIR systems”. In Proceedings of the 17th IFAC World Congress, Seoul, South Korea, July 2008. [pdf|link]

  8. C. R. Rojas, H. Hjalmarsson, L. Gerencsér, and J. Mårtensson. “Consistent estimation of real NMP zeros in stable LTI systems of arbitrary complexity”. In Proceedings of the 15th IFAC Symposium on System Identification (SYSID’09), Saint-Malo, France, 2009. [pdf|link]

  9. J. S. Welsh and C. R. Rojas. “A scenario based approach to robust experiment design”. In Proceedings of the 15th IFAC Symposium on System Identification (SYSID’09), Saint-Malo, France, 2009. [pdf|link]

  10. J. Mårtensson, C. R. Rojas, and H. Hjalmarsson. “Finite model order optimal input design for minimum variance control”. In Proceedings of the European Control Conference (ECC’09), Budapest, Hungary, 2009. [pdf]

  11. J. C. Agüero, C. R. Rojas, and G. C. Goodwin. “Fundamental limitations on the accuracy of MIMO linear models obtained by PEM for systems operating in open loop”. In Proceedings of the Joint 48th IEEE Conference on Decision and Control (CDC’09) and 28th Chinese Control Conference (CCC’09), Shanghai, China, 2009.

  12. C. Brighenti, B. Wahlberg, and C. R. Rojas. “Input design using Markov chains for system identification”. In Proceedings of the Joint 48th IEEE Conference on Decision and Control(CDC’09) and 28th Chinese Control Conference (CCC’09), Shanghai, China, 2009.

  13. E. Olofsson , H. Hjalmarsson, C. R. Rojas, P. Brunsell, and J. Drake. “Vector dither experiment design and direct parametric identification of reversed-field pinch normal modes”. In Proceedings of the Joint 48th IEEE Conference on Decision and Control (CDC’09) and 28th Chinese Control Conference (CCC’09), Shanghai, China, 2009. [pdf|link]

  14. C. R. Rojas and H. Hjalmarsson. “Input design for asymptotic robust \(\mathcal{H}_2\)-filtering”. In Proceedings of the Joint 48th IEEE Conference on Decision and Control (CDC’09) and 28th Chinese Control Conference (CCC’09), Shanghai, China, 2009. [pdf|link]

  15. C. R. Rojas, H. Hjalmarsson, and R. Hildebrand. “MIMO experiment design based on asymptotic model order theory”. In Proceedings of the Joint 48th IEEE Conference on Decision and Control (CDC’09) and 28th Chinese Control Conference (CCC’09), Shanghai, China, 2009. [pdf|link]

  16. E. Olofsson, C. R. Rojas, H. Hjalmarsson, P. Brunsell, and J. Drake. “Closed-loop MIMO ARX estimation of concurrent external plasma response eigenmodes in magnetic confinement fusion”. In Proceedings of the 49th IEEE Conference on Decision and Control (CDC’10), Atlanta, USA, 2010.

  17. C. Larsson, H. Hjalmarsson, and C. R. Rojas. “On optimal input design for nonlinear FIR-type systems”. In Proceedings of the 49th IEEE Conference on Decision and Control (CDC’10), Atlanta, USA, 2010.

  18. C. A. Larsson, H. Hjalmarsson, and C. R. Rojas. “Identification of Nonlinear Systems Using Misspecified Predictors”. In Proceedings of the 49th IEEE Conference on Decision and Control (CDC’10), Atlanta, USA, 2010.

  19. X. Bombois, A. J. den Dekker, C. R. Rojas, H. Hjalmarsson, and P. M. J. Van den Hof. “Optimal experiment design for hypothesis testing applied to functional magnetic resonance imaging”. In Proceedings of the 18th IFAC World Congress, Milano, Italy, August 2011.

  20. C. A. Larsson, C. R. Rojas, and H. Hjalmarsson. “MPC oriented experiment design”. In Proceedings of the 18th IFAC World Congress, Milano, Italy, August 2011.

  21. T. Oomen, C. R. Rojas, H. Hjalmarsson, and B. Wahlberg. “Analyzing iterations in identification with application to nonparametric \(\mathcal{H}_\infty\)-norm estimation”. In Proceedings of the 18th IFAC World Congress, Milano, Italy, August 2011.

  22. D. Katselis, M. Bengtsson, C. R. Rojas, H. Hjalmarsson, and E. Kofidis. “On preamble-based channel estimation in OFDMOQAM Systems”. In Proceedings of the 19th European Signal Processing Conference (EUSIPCO 2011)/, Barcelona, Spain, August 2011.

  23. B. Wahlberg, C. R. Rojas, and M. Annergren. “On \(\ell_1\) mean and variance filtering”. In Proceedings of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR), Pacific Grove, California, USA, 2011.

  24. E. Olofsson, C. R. Rojas, H. Hjalmarsson, P. Brunsell, and J. Drake. “Cascade and multibatch subspace system identification for multivariate vacuum-plasma response characterisation”. In Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC11), Orlando, USA, 2011.

  25. L. Huang, H. Hjalmarsson, and C. R. Rojas. “On consistent estimation of farthest NMP zeros of stable LTI systems”. In Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC11), Orlando, USA, 2011.

  26. B. Wahlberg, M. J. E. Annergren, and C. R. Rojas. “On optimal input signal design for identification of Output Error models”. In Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC11), Orlando, USA, 2011.

  27. C. R. Rojas and H. Hjalmarsson. “Sparse estimation based on a validation criterion”. In Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC11), Orlando, USA, 2011.

  28. C. R. Rojas, D. Katselis, H. Hjalmarsson, R. Hildebrand, and M. Bengtsson. “Chance constrained input design”. In Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC11), Orlando, USA, 2011. [pdf|link]

  29. C. R. Rojas. “Identifiability of multivariable dynamic errors-in-variables systems”. In Proceedings of the 9th IEEE International Conference on Control & Automation (IEEE ICCA’11), Santiago, Chile, 2011.

  30. D. Katselis, C. R. Rojas, H. Hjalmarsson, and M. Bengtsson. “A Chernoff convexification for chance constrained MIMO training sequence design”. In Proceedings of 13th IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2012), Cesme, Turkey, 2012.

  31. K. E. J. Olofsson and C. R. Rojas. “A practical approach to input design for modal analysis using subspace methods”. In Proceedings of the 16th IFAC Symposium on System Identification (SYSID 2012), Brussels, Belgium, 2012.

  32. H. Hjalmarsson, J. S. Welsh, and C. R. Rojas. “Identification of Box-Jenkins models using structured ARX models and nuclear norm relaxation”. In Proceedings of the 16th IFAC Symposium on System Identification (SYSID 2012), Brussels, Belgium, 2012.

  33. J. S. Welsh, C. R. Rojas, H. Hjalmarsson, and B. Wahlberg. “Sparse estimation for basis function selection in wideband system identification”. In Proceedings of the 16th IFAC Symposium on System Identification (SYSID 2012), Brussels, Belgium, 2012.

  34. R. Tóth, H. Hjalmarsson, and C. R. Rojas. “Sparse estimation of rational dynamic models”. In Proceedings of the 16th IFAC Symposium on System Identification (SYSID 2012), Brussels, Belgium, 2012.

  35. D. Eckhard, H. Hjalmarsson, C. R. Rojas, and M. Gevers. “Mean-squared error experiment design for linear regression models”. In Proceedings of the 16th IFAC Symposium on System Identification (SYSID 2012), Brussels, Belgium, 2012.

  36. D. Katselis, C. R. Rojas, J. S. Welsh, and H. Hjalmarsson. “Robust experiment design for system identification via semi-infinite programming techniques”. In Proceedings of the 16th IFAC Symposium on System Identification (SYSID 2012), Brussels, Belgium, 2012.

  37. D. Katselis, C. R. Rojas, H. Hjalmarsson, and M. Bengtsson. “Application-oriented finite sample experiment design: A semidefinite relaxation approach”. In Proceedings of the 16th IFAC Symposium on System Identification (SYSID 2012), Brussels, Belgium, 2012.

  38. D. Eckhard, A. S. Bazanella, C. R. Rojas, and H. Hjalmarsson. “On the convergence of the prediction error method to its global minimum”. In Proceedings of the 16th IFAC Symposium on System Identification (SYSID 2012), Brussels, Belgium, 2012.

  39. B. Wahlberg and C. R. Rojas. “On asymptotic frequency response variance expressions for estimated output error models”. In Proceedings of the 51st Conference on Decision and Control (CDC’12), Hawaii, USA, 2012.

  40. R. Tóth, H. Hjalmarsson, and C. R. Rojas. “Order and structural dependence selection of LPV-ARX models revisited”. In Proceedings of the 51st Conference on Decision and Control (CDC’12), Hawaii, USA, 2012.

  41. D. Katselis, C. R. Rojas, H. Hjalmarsson, and M. Bengtsson. “A Chernoff relaxation on the problem of application-oriented finite sample experiment design”. In Proceedings of the 51st Conference on Decision and Control (CDC’12), Hawaii, USA, 2012.

  42. T. Oomen, R. J. R. van der Maas, C. R. Rojas, and H. Hjalmarsson. “Iteratively learning the \(\mathcal{H}_\infty\)-norm of multivariable systems applied to model-error-modeling of a vibration isolation systems”. In Proceedings of the 2013 American Control Conference (ACC’2013), Washington, USA, 2013.

  43. D. Katselis, C. R. Rojas, and H. Hjalmarsson. “Application-oriented least squares experiment design in multicarrier communication systems”. In Proceedings of the 11th IFAC International Workshop on Adaptation and Learning in Control and Signal Processing (ALCOSP 2013), Caen, France, 2013. [pdf|link]

  44. C. R. Rojas, B. Wahlberg, and H. Hjalmarsson. “A sparse estimation technique for general model structures”. In Proceedings of the European Control Conference (ECC’13), Zurich, Switzerland, 2013.

  45. C. A. Larsson, H. Hjalmarsson, C. R. Rojas, X. Bombois, A. Mesbah, and P. E. Moden. “Model predictive control with integrated experiment design for output error systems”. In Proceedings of the European Control Conference (ECC’13), Zurich, Switzerland, 2013.

  46. V. Krishnamurthy, C. R. Rojas, and B. Wahlberg. “Computing monotone policies for Markov decision processes by exploiting sparsity”. In Proceedings of the 2013 Australian Control Conference (AUCC2013), Perth, Australia, 2013.

  47. P. E. Valenzuela, C. R. Rojas, and H. Hjalmarsson. “Optimal input design for non-linear dynamic systems: a graph theory approach”. In Proceedings of the 52nd IEEE Conference on Decision and Control (CDC’13), Florence, Italy, 2013.

  48. N. Everitt, H. Hjalmarsson, and C. R. Rojas. “A geometric approach to variance analysis of cascaded systems”. In Proceedings of the 52nd IEEE Conference on Decision and Control (CDC’13), Florence, Italy, 2013.

  49. B. I. Godoy, P. E. Valenzuela, C. R. Rojas, J. C. Agüero, and B. Ninness. “A novel input design approach for systems with quantized output data”. In Proceedings of the 13th European Control Conference (ECC’14), Strasbourg, France, 2014. [pdf]

  50. D. Katselis, C. R. Rojas, and H. Hjalmarsson. “Least Squares End Performance Experiment Design in Multicarrier Systems: The Sparse Preamble Case”. In Proceedings of the 13th European Control Conference (ECC’14), Strasbourg, France, 2014. [pdf]

  51. A. Ebadat, M. Annergren, C. A. Larsson, C. R. Rojas, B. Wahlberg, H. Hjalmarsson and J. Sjöberg. “Application Set Approximation in Optimal Input Design for Model Predictive Control”. In Proceedings of the 13th European Signal Processing Conference (ECC’14), Strasbourg, France, 2014. [pdf|arxiv]

  52. H. Hjalmarsson and C. R. Rojas. “Model structure selection – an update”. In Proceedings of the 13th European Control Conference (ECC’14), Strasbourg, France, 2014. [pdf]

  53. M. Sundin, S. Chatterjee, M. Jansson, and C. R. Rojas. “Relevance singular vector machine for low-rank matrix sensing”. In Proceedings of the International Conference on Signal Processing and Communications (SPCOM 2014), Bangalore, India, 2014. [pdf|arxiv]

  54. P. E. Valenzuela, J. Dahlin, C. R. Rojas and T. Schön. “A graph/particle-based method for experiment design in nonlinear systems”". In Proceedings of the 19th IFAC World Congress (IFAC’14), Cape Town, South Africa, 2014.

  55. A. Ebadat, B. Wahlberg, H. Hjalmarsson, C. R. Rojas, P. Hägg, and C. A. Larsson. “Applications oriented input design in time-domain through cyclic methods”. In Proceedings of the 19th IFAC World Congress (IFAC’14), Cape Town, South Africa, 2014. [arxiv]

  56. N. Everitt, C. R. Rojas and H. Hjalmarsson. “Variance Results for Parallel Cascade Serial Systems”. In Proceedings of the 19th IFAC World Congress (IFAC’14), Cape Town, South Africa, 2014.

  57. K. Li, C. R. Rojas, S. Chatterjee and H. Hjalmarsson. “Piecewise Toeplitz Matrices-based Sensing for Rank Minimization”. In Proceedings of the 22nd European Signal Processing Conference (EUSIPCO 2014), Lisbon, Portugal, 2014. [pdf|arxiv]

  58. A. Ebadat, P. E. Valenzuela, C. R. Rojas, H. Hjalmarsson, and B. Wahlberg. “Applications oriented input design for closed-loop system identification: A graph-theory approach”. In Proceedings of the 53rd IEEE Conference on Decision and Control (CDC’14), Los Angeles, California, USA, 2014.

  59. M. Galrinho, C. R. Rojas, and H. Hjalmarsson. “A weighted least-squares method for parameter estimation in structured models”. In Proceedings of the 53rd IEEE Conference on Decision and Control (CDC’14), Los Angeles, California, USA, 2014.

  60. N. Blomberg, C. R. Rojas, and B. Wahlberg. “Approximate regularization path for nuclear norm based \(\mathcal{H}_2\) model reduction”. In Proceedings of the 53rd IEEE Conference on Decision and Control (CDC’14), Los Angeles, California, USA, 2014. [arxiv]

  61. D. Katselis and C. R. Rojas. “Application-oriented estimator selection”. In Proceedings of the 40th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brisbane, Australia, 2015.

  62. C. R. Rojas and B. Wahlberg. “How to monitor and mitigate stair-casing in \(\ell_1\) trend filtering”. In Proceedings of the 40th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2015), Brisbane, Australia, 2015. [arxiv]

  63. D. Katselis, C. R. Rojas, and C. L. Beck. “Estimator selection: End-performance metric aspects”. In Proceedings of the 2015 American Control Conference (ACC 2015), Chicago, USA, 2015.

  64. D. Katselis, C. R. Rojas, B. I. Godoy, and J. C. Agüero. “On experiment design for single carrier and multicarrier systems”. In Proceedings of the European Control Conference (ECC’15), Linz, Austria, 2015.

  65. N. Blomberg, C. R. Rojas, and B. Wahlberg. “Approximate regularization paths for nuclear norm minimization using singular value bounds”. In Proceedings of the 2015 IEEE Signal Processing and Signal Processing Education Workshop, Salt Lake City, Utah, USA, 2015. [arxiv]

  66. C. R. Rojas, P. E. Valenzuela, and R. A. Rojas. “A critical view on benchmarks based on randomly generated systems”. In Proceedings of the 17th IFAC Symposium on System Identification (SYSID 2015), Beijing, China, 2015.

  67. N. Everitt, G. Bottegal, C. R. Rojas, and H. Hjalmarsson. “On the effect of noise correlation in parameter identification of SIMO systems”. In Proceedings of the 17th IFAC Symposium on System Identification (SYSID 2015), Beijing, China, 2015.

  68. P. E. Valenzuela, C. R. Rojas, and H. Hjalmarsson. “Uncertainty in system identification: learning from the theory of risk”. In Proceedings of the 17th IFAC Symposium on System Identification (SYSID 2015), Beijing, China, 2015.

  69. M. Galrinho, C. R. Rojas, and H. Hjalmarsson. “A least squares method for identification of feedback cascade systems”. In Proceedings of the 17th IFAC Symposium on System Identification (SYSID 2015), Beijing, China, 2015.

  70. R. Mattila, C. R. Rojas, and B. Wahlberg. “Evaluation of spectral learning for the identification of hidden Markov models”. In Proceedings of the 17th IFAC Symposium on System Identification (SYSID 2015), Beijing, China, 2015.

  71. H. Ha, J. Welsh, N. Blomberg, C. R. Rojas, and B. Wahlberg. “Reweighted nuclear norm regularization: A SPARSEVA approach”. In Proceedings of the 17th IFAC Symposium on System Identification (SYSID 2015), Beijing, China, 2015.

  72. M. Galrinho, C. R. Rojas, and H. Hjalmarsson. “On estimating initial conditions in unstructured models”. In Proceedings of the 54th IEEE Conference on Decision and Control (CDC’15), Osaka, Japan, 2015.

  73. N. Everitt, G. Bottegal, C. R. Rojas, and H. Hjalmarsson. “On the variance analysis of identified linear MIMO models”. In Proceedings of the 54th IEEE Conference on Decision and Control (CDC’15), Osaka, Japan, 2015.

  74. K. Li, C. R. Rojas, T. Yang, H. Hjalmarsson, K. H. Johansson, and S. Cong. “Piecewise sparse signal recovery via piecewise orthogonal matching pursuit”. In Proceedings of the 41th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Shanghai, China, 2016.

  75. P. E. Valenzuela, J. Dahlin, C. R. Rojas, and T. B. Schön. “Particle-based Gaussian process optimization for input design in nonlinear dynamical models”. In Proceedings of the 55th IEEE Conference on Decision and Control (CDC’16), 2016.

  76. M. Galrinho, C. R. Rojas, and H. Hjalmarsson. “A w\(\ell_2\)eighted least squares method for estimation of unstable systems”. In Proceedings of the 55th IEEE Conference on Decision and Control (CDC’16), 2016.

  77. N. Everitt, G. Bottegal, C. R. Rojas, and H. Hjalmarsson. “Identification of modules in dynamic networks: An empirical Bayes approach”. In Proceedings of the 55th IEEE Conference on Decision and Control (CDC’16), 2016.

  78. M. Müller, P. E. Valenzuela, and C. R. Rojas. “Risk-coherent \(\mathcal{H}_2\)-optimal disturbance rejection under model uncertainty”. In Proceedings of the 20th IFAC World Congress (IFAC WC 2017), Toulouse, France, 2017.

  79. R. Mattila, C. R. Rojas, V. Krishnamurthy, and B. Wahlberg. “Computing monotone policies for Markov decision processes: a nearly-isotonic penalty approach”. In Proceedings of the 20th IFAC World Congress (IFAC WC 2017), Toulouse, France, 2017. [arxiv]

  80. O. Trollberg, C. R. Rojas, and E. Jacobsen. “Online constraint adaptation in economic model predictive control”. In Proceedings of the 20th IFAC World Congress (IFAC WC 2017), Toulouse, France, 2017.

  81. R. Mattila, C. R. Rojas, V. Krishnamurthy, and B. Wahlberg. “Identification of hidden Markov models using spectral learning with likelihood maximization”. In Proceedings of the 56th IEEE Conference on Decision and Control (CDC 2017), Melbourne, Australia, 2017.

  82. M. I. Müller, P. E. Valenzuela, A. Proutiere, and C. R. Rojas. “A stochastic multi-armed bandit approach to nonparametric \(\mathcal{H}_\infty\) estimation”. In Proceedings of the 56th IEEE Conference on Decision and Control (CDC 2017), Melbourne, Australia, 2017.

  83. G. Rallo, S. Formentin, C. R. Rojas, T. Oomen, and S. M. Savaresi. “Data-driven \(\mathcal{H}_\infty\)-norm estimation via expert advice”. In Proceedings of the 56th IEEE Conference on Decision and Control (CDC 2017), Melbourne, Australia, 2017.

  84. R. Mattila, C. R. Rojas, V. Krishnamurthy, and B. Wahlberg. “Inverse Filtering for Hidden Markov Models”. In Proceedings of the Thirty-first Annual Conference on Neural Information Processing Systems (NIPS 2017), Long Beach, USA, 2017.

  85. T. Oomen and C. R. Rojas. “Sparse iterative learning control (SPILC): When to sample for resource-efficiency?”. In 15th International Workshop on Advanced Motion Control (AMC18), Tokyo, Japan, 2018.

  86. M. I. Müller and C. R. Rojas. “A Markov chain approach to compute the \(\ell_2\)-gain of nonlinear systems”. In Proceedings of the 18th IFAC Symposium on System Identification (SYSID 2018), Stockholm, Sweden, 2018.

  87. R. A. González and C. R. Rojas. “A fully Bayesian approach to kernel-based regularization for impulse response estimation”. In Proceedings of the 18th IFAC Symposium on System Identification (SYSID 2018), Stockholm, Sweden, 2018.

  88. M. R. H. Abdalmoaty, C. R. Rojas, and H. Hjalmarsson. “Identification of a class of nonlinear dynamical networks”. In Proceedings of the 18th IFAC Symposium on System Identification (SYSID 2018), Stockholm, Sweden, 2018.

  89. M. Sadeghi, C. R. Rojas, and B. Wahlberg. “A branch and bound approach to system identification based on fixed-rank Hankel matrix optimization”. In Proceedings of the 18th IFAC Symposium on System Identification (SYSID 2018), Stockholm, Sweden, 2018.

  90. O. Mazhar, C. R. Rojas, C. Fischione, and M. Hesamzadeh. “Bayesian model selection for change point detection and clustering”. In Proceedings of the Thirty-fifth International Conference on Machine Learning (ICML 2018), Stockholm, Sweden, 2018.

  91. M. I. Müller, J. Milosevic, H. Sandberg, and C. R. Rojas. “A risk-theoretical approach to \(\mathcal{H}_2\)-optimal control under covert attacks”. In Proceedings of the 57th IEEE Conference on Decision and Control (CDC 2018), Fontainebleau, Miami Beach, USA, 2018.

  92. R. A. González, C. R. Rojas, and J S. Welsh. “An asymptotically optimal indirect approach to continuous-time system identification”. In Proceedings of the 57th IEEE Conference on Decision and Control (CDC 2018), Fontainebleau, Miami Beach, USA, 2018. [arxiv]

  93. G. Rallo, S. Formentin, C. R. Rojas, and S. M. Savaresi. “Robust experiment design for virtual reference feedback tuning”. In Proceedings of the 57th IEEE Conference on Decision and Control (CDC 2018), Fontainebleau, Miami Beach, USA, 2018.

  94. R. Mattila, C. R. Rojas, V. Krishnamurthy, and B. Wahlberg. “Inverse filtering for linear gaussian state-space models”. In Proceedings of the 57th IEEE Conference on Decision and Control (CDC 2018), Fontainebleau, Miami Beach, USA, 2018.

  95. M. I. Müller and C. R. Rojas. “Gain estimation of linear dynamical systems using Thompson Sampling”. In Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS 2019), Naha, Okinawa, Japan, 2019.

  96. M. I. Müller and C. R. Rojas. “Risk-coherent \(\mathcal{H}_\infty\)-optimal filter design under model uncertainty with applications to MISO control”. In Proceedings of the European Control Conference (ECC19), Naples, Italy, 2019.

  97. R. Mattila, I. Lourenço, V. Krishnamurthy, C. R. Rojas, and B. Wahlberg. “What did your adversary believe? Optimal smoothing in counter-autonomous systems”. In Proceedings of the 45th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2020), Barcelona, Spain, 2020. [arxiv]

  98. R. A. González and C. R. Rojas. “Finite sample deviation and variance bounds for first order autoregressive processes”. In Proceedings of the 45th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2020), Barcelona, Spain, 2020. [arxiv]

  99. R. A. González and C. R. Rojas. “A finite-sample deviation bound for stable autoregressive processes”. In Proceedings of the 2nd Conference on Learning for Decision and Control (L4DC), Berkeley, USA, 2020. [arxiv]

  100. R. A. González, J. S. Welsh, and C. R. Rojas. “Enforcing stability through ellipsoidal inner approximations in the indirect approach for continuous-time system identification”. In Proceedings of the 21st IFAC World Congress (IFAC 2020), Berlin, Germany, 2020.

  101. R. Mattila, C. R. Rojas, E. Moulines, V. Krishnamurthy, and B. Wahlberg. “Fast and consistent learning of hidden Markov models by incorporating non-consecutive correlations”. In Proceedings of the 37th International Conference on Machine Learning (ICML 2020), 2020.

  102. M. I. Müller and C. R. Rojas. "Iterative \(\mathcal{H}_\infty\)-norm estimation using cyclic-prefixed signals’’. In Proceedings of the 59th Conference on Decision and Control (CDC 2020), 2020.

  103. I. Lourenço, R. Mattila, C. R. Rojas, and B. Wahlberg. “How to protect your privacy? A framework for counter-adversarial decision making”. In Proceedings of the 59th IEEE Conference on Decision and Control (CDC 2020), 2020. [arxiv]

  104. M. I. Müller, A. Koch, F. Allgower, and C. R. Rojas. “Data-driven input-passivity estimation using power iterations”. In Proceedings of the 19th IFAC Symposium on System Identification (SYSID 2021), 2021.

  105. I. Lourenço, R. Mattila, C. R. Rojas, and B. Wahlberg. “Cooperative system identification via correctional learning”. In Proceedings of the 19th IFAC Symposium on System Identification (SYSID 2021), 2021. [arxiv]

  106. R. A. González, C. R. Rojas, and H. Hjalmarsson. “Non-causal regularized least-squares for continuous-time system identification with band-limited input excitations”. In Proceedings of the 60th IEEE Conference on Decision and Control (CDC 2021), 2021. [arxiv]

  107. R. A. González, C. R. Rojas, S. Pan, and J. S. Welsh. “The SRIVC algorithm for continuous-time system identification with arbitrary input excitation in open and closed loop”. In Proceedings of the 60th IEEE Conference on Decision and Control (CDC 2021), 2021.

  108. J. Parsa, C. R. Rojas, and H. Hjalmarsson. ’'Optimal input design for sparse system identification’’. In Proceedings of the 2022 European Control Conference (ECC), 2022.

  109. B. Lakshminarayanan and C. R. Rojas. “A statistical decision-theoretical perspective on the two-stage approach to parameter estimation”. In Proceedings of the 61th IEEE Conference on Decision and Control (CDC 2022), 2022. [arxiv]

  110. I. Lourenço, R. Winqvist, C. R. Rojas, and B. Wahlberg. ’'A teacher-student Markov decision process-based framework for online correctional learning’’. In Proceedings of the 61th IEEE Conference on Decision and Control (CDC 2022), 2022. [arxiv]

  111. R. A. González, A. L. Cedeño, M. Coronel, J. C. Agüero, and C. R. Rojas. “An EM algorithm for Lebesgue-sampled state-space continuous-time system identification”. In Proceedings of the IFAC World Congress 2023 (IFAC WC 2023), 2023.

  112. B. Lakshminarayanan and C. R. Rojas. “A unified approach to differentially private Bayes point estimation”. In Proceedings of the IFAC World Congress 2023 (IFAC WC 2023), 2023.

  113. R. A. González, C. R. Rojas, S. Pan, and J. S. Welsh. “Parsimonious identification of continuous-time systems: A block-coordinate descent approach”. In Proceedings of the IFAC World Congress 2023 (IFAC WC 2023), 2023.

  114. A. Elton, R. A. González, J. S. Welsh, T. Oomen, and C. R. Rojas. “Blind non-parametric estimation of SISO continuous-time systems”. In Proceedings of the IFAC World Congress 2023 (IFAC WC 2023), 2023.

  115. F. Quinzan, A. Soleymani, P. Jaillet, C. R. Rojas, and S. Bauer. “DRCFS: Doubly robust causal feature selection”. In Proceedings of the Fortieth International Conference on Machine Learning (ICML 2023), 2023.

  116. B. Lakshminarayanan and C. R. Rojas. “Minimax two-stage gradient boosting for parameter estimation”. In Proceedings of the 62nd IEEE Conference on Decision and Control (CDC 2023), 2023.

  117. R. Winqvist, I. Lourenço, F. Quinzan, C. R. Rojas, and B. Wahlberg. “Optimal transport for correctional learning”. In Proceedings of the 62nd IEEE Conference on Decision and Control (CDC 2023), 2023.

  118. I. Lourenço, A. Bobu, C. R. Rojas, and B. Wahlberg. “Diagnosing and augmenting feature representations in correctional inverse reinforcement learning”. In Proceedings of the 62nd IEEE Conference on Decision and Control (CDC 2023), 2023.

  119. A. Elton, R. A. González, J. S. Welsh, C. R. Rojas, and M. Fu. “Parametric continuous-time blind system identification”. In Proceedings of the 62nd IEEE Conference on Decision and Control (CDC 2023), 2023.

  120. F. Dettù, B. Lakshminarayanan, S. Formentin, and C. R. Rojas. “From data to control: A two-stage simulation-based approach”. In Proceedings of the 2024 European Control Conference (ECC) (accepted for publication), 2024.

  121. P. Zufiria, I. Fernández-Sánchez-Pascuala, and C. R. Rojas. “Multicriteria model-agnostic counterfactual explainability for classifiers”. In Proceedings of the 2024 International Joint Conference on Neural Networks (IJCNN) (accepted for publication), 2024.

  122. J. He, C. R. Rojas, and H. Hjalmarsson. “Weighted least-squares PARSIM”. In Proceedings of the 20th IFAC Symposium on System Identification (SYSID 2024) (accepted for publication), 2024.

  123. J. He, C. R. Rojas, and H. Hjalmarsson. “A weighted least-squares method for non-asymptotic identification of Markov parameters from multiple trajectories”. In Proceedings of the 20th IFAC Symposium on System Identification (SYSID 2024) (accepted for publication), 2024.

  124. K. Colin, Y. Ju, X. Bombois, C. R. Rojas, and H. Hjalmarsson. “A bias-variance perspective of data-driven control”. In Proceedings of the 20th IFAC Symposium on System Identification (SYSID 2024) (accepted for publication), 2024.

  125. D. Materassi, S. Warnick, C. R. Rojas, M. Schoukens, and E. Cross. “Explaining complex systems: A tutorial on transparency and interpretability in machine learning models (part I)”. In Proceedings of the 20th IFAC Symposium on System Identification (SYSID 2024) (accepted for publication), 2024.

  126. D. Materassi, S. Warnick, C. R. Rojas, M. Schoukens, and E. Cross. “Explaining complex systems: A tutorial on transparency and interpretability in machine learning models (part II)”. In Proceedings of the 20th IFAC Symposium on System Identification (SYSID 2024) (accepted for publication), 2024.

  127. K. Kowalczyk, P. Wachel and C. R. Rojas. “Kernel-based learning with guarantees for multi-agent applications”. In Proceedings of the 24th International Conference on Computational Science (ICCS 2024) (accepted for publication), 2024.

Book Chapters

  1. G. C. Goodwin, C. R. Rojas, and J. S. Welsh. “Good, bad and optimal experiments for identification”. In T. Glad, editor, Forever Ljung in System Identification – Workshop on the occasion of Lennart Ljung's 60th birthday. September 2006. [pdf]

  2. C. R. Rojas, G. C. Goodwin, M. M. Seron, and M. Zhang. “Open-cut mine planning via closed-loop receding-horizon optimal control”. In R. S. Sánchez-Peña, J. Quevedo, and V. Puig, editors, Identification and Control: The Gap between Theory and Practice, pages 43-62. Springer, London, 2007. [pdf|link]

  3. C. R. Rojas, J. Mårtensson, and H. Hjalmarsson. “A tutorial on applications-oriented optimal experiment design”. In D. Alberer H. Hjalmarsson, and L. del Re, editors, Identification for Automotive Systems, pages 149-164. Springer, 2012. [pdf|link]

  4. C. R. Rojas and M. Müller. “Algorithms for data-driven \(\mathcal{H}_\infty\)-norm estimation”. In C. Novara and S. Formentin, editors, Data-Driven Modelling, Filtering and Control: Methods and Applications, pages 145-163. IET Publishing, 2019.

Submitted Journal Papers

  1. J. Parsa, C. R. Rojas, and H. Hjalmarsson. “Coherence-based input design for sparse system identification”. IEEE Transactions on Automatic Control (submitted for publication), 2023.

  2. R. A. González, K. Classens, C. R. Rojas, J. Welsh, and T. Oomen. “Identification of additive continuous-time systems in open and closed-loop”. Automatica (submitted for publication), 2023.

  3. J. Parsa, C. R. Rojas, and H. Hjalmarsson. “Reducing computational complexity in nonlinear model input design via sparse estimation”. Automatica (submitted for publication), 2024.

  4. B. Lakshminarayanan, F. Dettù, C. R. Rojas, and S. Formentin. “An inverse learning paradigm for controller tuning rules”. Automatica (submitted for publication), 2024.

  5. P. E. Valenzuela, B. I. Godoy, and C. R. Rojas. “On robust input design for identification of FIR systems with quantized measurements”. IEEE Signal Processing Letters (submitted for publication), 2016.

  6. C. R. Rojas and B. Wahlberg. “On change point detection using the fused lasso method”. Annals of Statistics (submitted for publication), 2014. [arxiv]

Submitted Conference Papers

  1. J. He, I. Ziemann, C. R. Rojas, and H. Hjalmarsson. “Finite sample analysis for a class of subspace identification methods”. In Proceedings of the 63nd IEEE Confer- ence on Decision and Control (CDC 2024) (submitted for publication), 2024.

PhD Thesis

  1. C. R. Rojas. Robust Experiment Design. The University of Newcastle, Australia, 2008. [pdf]