Fetching the paper…
Reading the bibliography…
In this work, we consider compressed sensing reconstruction from $M$ measurements of $K$-sparse structured signals which do not possess a writable correlation model.
P. Smolensky, Information Processing in Dynamical Systems: Foundations of Harmony Theory , ser. Parallel Distributed Porcessing: Explorations in the Microsctructure of Cognition. MIT Press, 1986, ch. 6, pp. 194–281
1986
Earlier work this paper cites.
Y. LeCun, L. Bottu, Y. Bengio, and P. Haffner, “Gradient-based learning applied to document recognition,” Proc. of the IEEE , vol. 86, no. 11, pp. 2278–2324, November 1998
1998
Earlier work this paper cites.
G. E. Hinton, “Training products of experts by minimizing contrastive divergence,” Neural Computation , vol. 14, no. 8, pp. 1771–1800, 2002
2002
Earlier work this paper cites.
T. Heskes, “Stable fixed points of loopy belief propagation are minima of the Bethe free energy,” in Advances in Neural Information Processing Systems , vol. 15, 2002, pp. 359–366
2002
Earlier work this paper cites.
E. Candès and J. Romberg, “Signal recovery from random projections,” in Computational Imaging III . Proc. SPIE 5674, Mar. 2005, pp. 76–86
2005
Earlier work this paper cites.
D. L. Donoho, “Compressed sensing,” IEEE Trans. on Information Theory , vol. 52, no. 4, pp. 1289–1306, Apr. 2006
2006
Earlier work this paper cites.
D. Takhar, J. N. Laska, M. B. Wakin, M. F. Duarte, D. Baron, S. Sarvotham, K. F. Kelly, and R. G. Baraniuk, “A new compressive imaging camera architecture using optical-domain compression,” in Computational Imaging IV . Proc. SPIE 6065, 2006, p. 606509
2006
Earlier work this paper cites.
D. L. Donoho, Y. Tsaig, I. Drori, and J.-L. Starck, “Sparse solution of underdetermined linear equations by stagewise orthogonal matching pursuit,” Stanford University, Tech. Rep., 2006
2006
Earlier work this paper cites.
D. L. Donoho and J. Tanner, “Thresholds for the recovery of sparse solutions via l1 minimization,” in Information Sciences and Systems, Proc. Annual Conference on , 2006, pp. 202–206
2006
Earlier work this paper cites.
E. J. Candès and M. B. Wakin, “An introduction to compressive sampling,” IEEE Signal Processing Magazine , vol. 25, no. 2, pp. 21–30, 2008
2008
Earlier work this paper cites.
T. T. Do, L. Gan, N. Nguyen, and T. D. Tran, “Sparsity adaptive matching pursuit algorithm for practical compressed sensing,” in Proc. Asilomar Conf. on Signals, Systems, and Computers , Pacific Grove, California, Oct. 2008, pp. 581–587
2008
Cited alongside, same era.
D. Baron, S. Sarvotham, and R. G. Baraniuk, “Bayesian compressive sensing via belief propagation,” IEEE Trans. on Signal Processing , vol. 58, no. 1, pp. 269–280, 2009
2009
Cited alongside, same era.
D. L. Donoho, A. Maleki, and A. Montanari, “Message-passing algorithms for compressed sensing,” Proc. Nat. Academy of Sciences of the U.S.A. , vol. 106, no. 45, p. 18914, 2009
2009
Cited alongside, same era.
S. Rangan, “Estimation with random linear mixing, belief propagation and compressed sensing,” in Proc. Annual Conf. on Information Sciences and Systems , 2010, pp. 1–6
2010
Cited alongside, same era.
——, “Statistical physics-based reconstruction in compressed sensing,” Phys. Rev. X , vol. 2, p. 021005, 2012
2012
Later among the works it cites.
A. Drémeau, C. Herzet, and L. Daudet, “Boltzmann machine and mean-field approximation for structured sparse decompositions,” IEEE Trans. on Signal Processing , vol. 60, no. 7, pp. 3425–3438, 2012
2012
Later among the works it cites.
Z. Zhang, Y. Xu, J. Yang, X. Li, and D. Zhang, “A survey of sparse representation: Algorithms and applications,” IEEE Access , vol. 3, pp. 290–530, 2015
2015
Later among the works it cites.
2015
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
——, “Message passing algorithms for compressed sensing: II. analysis and validation,” in Proc. IEEE Info. Theory Workshop , Cairo, Egypt, 2010, pp. 1–5
2010
Cited alongside, same era.
P. Schniter, “Turbo reconstruction of structured sparse signals,” in Proc. Conf. on Info. Sciences and Systems , 2010, pp. 1–6
2010
Cited alongside, same era.
M. Mishali, Y. C. Eldar, O. Dounaevsky, and E. Shoshan, “Xampling: Analog to digital at sub-Nyquist rates,” IET Circuits, Devices and Systems , vol. 5, no. 1, pp. 8–20, January 2011
2011
Cited alongside, same era.
S. Rangan, “Generalized approximate message passing for estimation with random linear mixing,” in Proc. IEEE Intl. Symp. on Info. Theory , 2011, p. 2168
2011
Cited alongside, same era.
2011
Cited alongside, same era.
F. Krzakala, M. Mézard, F. Sausset, Y. Sun, and L. Zdeborová, “Probabilistic reconstruction in compressed sensing: Algorithms, phase diagrams, and threshold achieving matrices,” Journal of Statistical Mechanics: Theory and Experiment , vol. 2012, no. 8, p. P08009, 2012
2012
Cited alongside, same era.
2015
Later among the works it cites.
M. Gabrié, E. W. Tramel, and F. Krzakala, “Training restricted Boltzmann machines via the Thouless-Andreson-Palmer free energy,” in Advances in Neural Information Processing System , vol. 28, Montreal, Canada, June 2015, pp. 640–648
2015
Later among the works it cites.
H. Huang and T. Toyoizumi, “Advanced mean-field theory of restricted Boltzmann machine,” Physical Review E , vol. 91, no. 5, p. 050101, 2015
2015
Later among the works it cites.
E. W. Tramel, A. Drémeau, and F. Krzakala, “Approximate message passing with restricted Boltzmann machine priors,” Journal of Statistical Mechanics: Theory and Experiment , 2016, to appear
2016
Closest in time.