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Automatica (Oxford), ISSN 0005-1098, 03/2014, Volume 50, Issue 3, pp. 657 - 682
.... In particular, maximum likelihood and prediction error methods represent the mainstream approaches to identification of linear dynamic systems, with a long history of theoretical and algorithmic contributions... 
Linear system identification | Inverse problems | Model complexity selection | Bias-variance trade-off | Kernel-based regularization | Gaussian processes | Prediction error methods | Reproducing kernel Hilbert spaces | Engineering, Electrical & Electronic | Engineering | Automation & Control Systems | Technology | Science & Technology
Journal Article
Journal of scientific computing, ISSN 0885-7474, 2/2013, Volume 54, Issue 2, pp. 269 - 310
Journal Article
Acta numerica, ISSN 0962-4929, 05/2018, Volume 27, pp. 1 - 111
Regularization methods are a key tool in the solution of inverse problems. They are used to introduce prior knowledge and allow a robust approximation of ill-posed (pseudo-) inverses... 
Physical Sciences | Mathematics | Science & Technology | Medical imaging | Inverse problems | Partial differential equations | Image processing | Variational methods | Noise | Applied mathematics | Regularization methods | Learning theory | Banach spaces | Ill posed problems | Regularization
Journal Article
IEEE journal of selected topics in signal processing, ISSN 1932-4553, 12/2007, Volume 1, Issue 4, pp. 606 - 617
Recently, a lot of attention has been paid to regularization based methods for sparse signal reconstruction (e.g... 
Convex optimization | regularization | Basis pursuit denoising | Least squares | Preconditioned conjugate gradients | Interior-point methods | Compressive sampling | Compressed sensing | Studies | Methods | Algorithms
Journal Article