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In this paper, we study the system identification problem for sparse linear time-invariant systems.
L. Ljung, “Convergence analysis of parametric identification methods,” IEEE transactions on automatic control , vol. 23, no. 5, pp. 770–783, 1978
1978
Earlier work this paper cites.
D. R. Cox and D. V. Hinkley, Theoretical statistics . CRC Press, 1979
1979
Earlier work this paper cites.
L. Ljung, “System identification,” in Signal analysis and prediction . Springer, 1998, pp. 163–173
1998
Earlier work this paper cites.
E. Weyer, R. C. Williamson, and I. M. Mareels, “Finite sample properties of linear model identification,” IEEE Transactions on Automatic Control , vol. 44, no. 7, pp. 1370–1383, 1999
1999
Earlier work this paper cites.
E. Weyer, “Finite sample properties of system identification of arx models under mixing conditions,” Automatica , vol. 36, no. 9, pp. 1291–1299, 2000
2000
Earlier work this paper cites.
I. M. Johnstone, “On the distribution of the largest eigenvalue in principal components analysis,” Annals of statistics , pp. 295–327, 2001
2001
Earlier work this paper cites.
P. Zhao and B. Yu, “On model selection consistency of lasso,” Journal of Machine learning research , vol. 7, no. Nov, pp. 2541–2563, 2006
2006
Earlier work this paper cites.
N. Meinshausen and P. Bühlmann, “High-dimensional graphs and variable selection with the lasso,” The annals of statistics , pp. 1436–1462, 2006
2006
Earlier work this paper cites.
D. L. Donoho, “For most large underdetermined systems of linear equations the minimal 𝓁1-norm solution is also the sparsest solution,” Communications on pure and applied mathematics , vol. 59, no. 6, pp. 797–829, 2006
2006
Earlier work this paper cites.
E. Candes and J. Romberg, “Sparsity and incoherence in compressive sampling,” Inverse problems , vol. 23, no. 3, p. 969, 2007
2007
Earlier work this paper cites.
M. J. Wainwright, “Sharp thresholds for high-dimensional and noisy sparsity recovery using ℓ 1 \ell_{1} -constrained quadratic programming (lasso),” IEEE transactions on information theory , vol. 55, no. 5, pp. 2183–2202, 2009
2009
Earlier work this paper cites.
E.-W. Bai, “Non-parametric nonlinear system identification: An asymptotic minimum mean squared error estimator,” IEEE Transactions on automatic control , vol. 55, no. 7, pp. 1615–1626, 2010
2010
Earlier work this paper cites.
J. Pereira, M. Ibrahimi, and A. Montanari, “Learning networks of stochastic differential equations,” in Advances in Neural Information Processing Systems , 2010, pp. 172–180
2010
Earlier work this paper cites.
M. Mesbahi and M. Egerstedt, Graph theoretic methods in multiagent networks . Princeton University Press, 2010
2010
Cited alongside, same era.
Z. Hou and S. Jin, “Data-driven model-free adaptive control for a class of mimo nonlinear discrete-time systems,” IEEE Transactions on Neural Networks , vol. 22, no. 12, pp. 2173–2188, 2011
2011
Cited alongside, same era.
S. N. Negahban and M. J. Wainwright, “Simultaneous support recovery in high dimensions: Benefits and perils of block ℓ 1 / ℓ ∞ \ell_{1}/\ell_{\infty} -regularization,” IEEE Transactions on Information Theory , vol. 57, no. 6, pp. 3841–3863, 2011
2011
Cited alongside, same era.
R. Pintelon and J. Schoukens, System identification: a frequency domain approach . John Wiley & Sons, 2012
2012
Cited alongside, same era.
R. S. Smith, “Frequency domain subspace identification using nuclear norm minimization and hankel matrix realizations,” IEEE Transactions on Automatic Control , vol. 59, no. 11, pp. 2886–2896, 2014
2014
Later among the works it cites.
Y.-S. Wang, N. Matni, and J. C. Doyle, “Localized LQR optimal control,” in IEEE 53rd Conference on Decision and Control , 2014, pp. 1661–1668
2014
Later among the works it cites.
K. Chernyshov, “Towards the knowledge-based multi-agent system identification,” in IEEE 10th Conference on Industrial Electronics and Applications , 2015, pp. 399–404
2015
Later among the works it cites.
N. Omranian, J. M. Eloundou-Mbebi, B. Mueller-Roeber, and Z. Nikoloski, “Gene regulatory network inference using fused lasso on multiple data sets,” Scientific reports , vol. 6, p. 20533, 2016
2016
Later among the works it cites.
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2012
Cited alongside, same era.
S. Sun, R. Huang, and Y. Gao, “Network-scale traffic modeling and forecasting with graphical lasso and neural networks,” Journal of Transportation Engineering , vol. 138, no. 11, pp. 1358–1367, 2012
2012
Cited alongside, same era.
2012
Cited alongside, same era.
F. Lin, M. Fardad, and M. R. Jovanović, “Design of optimal sparse feedback gains via the alternating direction method of multipliers,” IEEE Transactions on Automatic Control , vol. 58, no. 9, pp. 2426–2431, 2013
2013
Cited alongside, same era.
V. L. Le, F. Lauer, and G. Bloch, “Selective ℓ 1 \ell_{1} minimization for sparse recovery,” IEEE Transactions on Automatic Control , vol. 59, no. 11, pp. 3008–3013, 2014
2014
Cited alongside, same era.
B. M. Sanandaji, M. B. Wakin, and T. L. Vincent, “Observability with random observations,” IEEE Transactions on Automatic Control , vol. 59, no. 11, pp. 3002–3007, 2014
2014
Cited alongside, same era.
X. Jiang, Y. Yao, H. Liu, and L. Guibas, “Compressive network analysis,” IEEE transactions on automatic control , vol. 59, no. 11, pp. 2946–2961, 2014
2014
Cited alongside, same era.
C. R. Rojas, R. Tóth, and H. Hjalmarsson, “Sparse estimation of polynomial and rational dynamical models.” IEEE Trans. Automat. Contr. , vol. 59, no. 11, pp. 2962–2977, 2014
2014
Cited alongside, same era.
S. Hassan-Moghaddam, N. K. Dhingra, and M. R. Jovanović, “Topology identification of undirected consensus networks via sparse inverse covariance estimation,” in IEEE 55th Conference on Decision and Control , 2016, pp. 4624–4629
2016
Later among the works it cites.
2017
Later among the works it cites.
2017
Later among the works it cites.
G. Fazelnia, R. Madani, A. Kalbat, and J. Lavaei, “Convex relaxation for optimal distributed control problems,” IEEE Transactions on Automatic Control , vol. 62, no. 1, pp. 206–221, 2017
2017
Later among the works it cites.
2017
Later among the works it cites.
S. Sadraddini and C. Belta, “Formal guarantees in data-driven model identification and control synthesis,” in 21st ACM International Conference on Hybrid Systems: Computation and Control . ACM, 2018
2018
Closest in time.
S. Fattahi and S. Sojoudi, “Data-driven sparse system identification,” to appear in IEEE 57th Conference on Decision and Control , 2018
2018
Closest in time.
S. Fattahi and S. Sojoudi, “Non-asymptotic analysis of block-regularized regression problem,” to appear in 56th Annual Allerton Conference on Communication, Control, and Computing , 2018
2018
Closest in time.
G. Darivianakis, S. Fattahi, J. Lygeros, and J. Lavaei, “High-performance cooperative distributed model predictive control for linear systems,” American Control Conference , 2018
2018
Closest in time.