Universal FIR MMSE Filtering
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[1] Yonina C. Eldar,et al. A competitive minimax approach to robust estimation of random parameters , 2004, IEEE Transactions on Signal Processing.
[2] Tsachy Weissman,et al. Universal Denoising of Discrete-Time Continuous-Amplitude Signals , 2006, IEEE Transactions on Information Theory.
[3] Andrew C. Singer,et al. Universal Switching Linear Least Squares Prediction , 2008, IEEE Transactions on Signal Processing.
[4] Tsachy Weissman,et al. Universal Filtering Via Hidden Markov Modeling , 2008, IEEE Transactions on Information Theory.
[5] Georg Zeitler,et al. Universal Piecewise Linear Prediction Via Context Trees , 2007, IEEE Transactions on Signal Processing.
[6] H. Poor. On robust wiener filtering , 1980 .
[7] Andrew C. Singer,et al. Universal Linear Least-Squares Prediction in the Presence of Noise , 2007, 2007 IEEE/SP 14th Workshop on Statistical Signal Processing.
[8] Norbert Wiener,et al. Extrapolation, Interpolation, and Smoothing of Stationary Time Series , 1964 .
[9] Tsachy Weissman,et al. Universal prediction of individual binary sequences in the presence of noise , 2001, IEEE Trans. Inf. Theory.
[10] Charles R. Johnson,et al. Matrix analysis , 1985, Statistical Inference for Engineers and Data Scientists.
[11] C. Stein,et al. Estimation with Quadratic Loss , 1992 .
[12] Elad Hazan,et al. Logarithmic regret algorithms for online convex optimization , 2006, Machine Learning.
[13] J. V. Ryzin,et al. The Compound Decision Problem with $m \times n$ Finite Loss Matrix , 1966 .
[14] H. Robbins. Asymptotically Subminimax Solutions of Compound Statistical Decision Problems , 1985 .
[15] Yonina C. Eldar,et al. Linear minimax regret estimation of deterministic parameters with bounded data uncertainties , 2004, IEEE Transactions on Signal Processing.
[16] J. V. Ryzin,et al. The Sequential Compound Decision Problem with $m \times n$ Finite Loss Matrix , 1966 .
[17] Tsachy Weissman,et al. Discrete Denoising With Shifts , 2007, IEEE Transactions on Information Theory.
[18] Tsachy Weissman,et al. Universal discrete denoising: known channel , 2003, IEEE Transactions on Information Theory.
[19] Andrew C. Singer,et al. Universal linear least squares prediction: Upper and lower bounds , 2002, IEEE Trans. Inf. Theory.
[20] Norbert Wiener,et al. Extrapolation, Interpolation, and Smoothing of Stationary Time Series, with Engineering Applications , 1949 .
[21] S. Haykin,et al. Adaptive Filter Theory , 1986 .
[22] V. Vovk. Competitive On‐line Statistics , 2001 .
[23] Gábor Lugosi,et al. Prediction, learning, and games , 2006 .
[24] Martin Zinkevich,et al. Online Convex Programming and Generalized Infinitesimal Gradient Ascent , 2003, ICML.
[25] Neri Merhav,et al. Universal Prediction , 1998, IEEE Trans. Inf. Theory.
[26] Tsachy Weissman,et al. Competitive On-line Linear FIR MMSE Filtering , 2007, 2007 IEEE International Symposium on Information Theory.
[27] Neri Merhav,et al. Universal Filtering Via Prediction , 2007, IEEE Transactions on Information Theory.
[28] Abraham Lempel,et al. Compression of individual sequences via variable-rate coding , 1978, IEEE Trans. Inf. Theory.
[29] Ludwig Elsner,et al. On the variation of the spectra of matrices , 1982 .
[30] Neri Merhav,et al. Universal prediction of individual sequences , 1992, IEEE Trans. Inf. Theory.
[31] S. Vardeman. Admissible solutions of k-extended finite state set and sequence compound decision problems , 1980 .
[32] I. Johnstone,et al. Adapting to Unknown Smoothness via Wavelet Shrinkage , 1995 .