-
1
-
-
31744440684
-
Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information
-
Feb.
-
E. J. Candes, J. Romberg, and T. Tao, "Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information," IEEE Trans. Inform. Theory, vol. 52, no. 2, pp. 489-509, Feb. 2006.
-
(2006)
IEEE Trans. Inform. Theory
, vol.52
, Issue.2
, pp. 489-509
-
-
Candes, E.J.1
Romberg, J.2
Tao, T.3
-
2
-
-
85032751965
-
Compressive sensing [lecture notes]
-
R. G. Baraniuk, "Compressive sensing [lecture notes]," IEEE Signal Processing Mag., vol. 24, no. 4, pp. 118-121, 2007.
-
(2007)
IEEE Signal Processing Mag.
, vol.24
, Issue.4
, pp. 118-121
-
-
Baraniuk, R.G.1
-
3
-
-
62749175137
-
CoSaMP: Iterative signal recovery from incomplete and inaccurate samples
-
D. Needell and J. A. Tropp, "CoSaMP: Iterative signal recovery from incomplete and inaccurate samples," Appl. Comput. Harmon. Anal., vol. 26, no. 3, pp. 301-321, 2009.
-
(2009)
Appl. Comput. Harmon. Anal.
, vol.26
, Issue.3
, pp. 301-321
-
-
Needell, D.1
Tropp, J.A.2
-
4
-
-
7044231546
-
An iterative thresholding algorithm for linear inverse problems with a sparsity constraint
-
I. Daubechies, M. Defrise, and C. D. Mol, "An iterative thresholding algorithm for linear inverse problems with a sparsity constraint," Comm. on Pure and Applied Math., vol. 75, pp. 1412-1457, 2004.
-
(2004)
Comm. on Pure and Applied Math.
, vol.75
, pp. 1412-1457
-
-
Daubechies, I.1
Defrise, M.2
Mol, C.D.3
-
5
-
-
73149095169
-
Message passing algorithms for compressed sensing
-
D. L. Donoho, A. Maleki, and A. Montanari, "Message passing algorithms for compressed sensing," Proc. Natl. Acad. Sci., vol. 106, no. 45, pp. 18914-18919, 2009.
-
(2009)
Proc. Natl. Acad. Sci.
, vol.106
, Issue.45
, pp. 18914-18919
-
-
Donoho, D.L.1
Maleki, A.2
Montanari, A.3
-
7
-
-
84881059377
-
User's guide for TVAL3: TV minimization by augmented lagrangian and alternating direction algorithms
-
C. Li, W. Yin, and Y. Zhang, "User's guide for TVAL3: TV minimization by augmented Lagrangian and alternating direction algorithms," Rice CAAM Department report, vol. 20, pp. 46-47, 2009.
-
(2009)
Rice CAAM Department Report
, vol.20
, pp. 46-47
-
-
Li, C.1
Yin, W.2
Zhang, Y.3
-
8
-
-
77950244328
-
Model-based compressive sensing
-
Apr.
-
R. G. Baraniuk, V. Cevher, M. F. Duarte, and C. Hegde, "Model-based compressive sensing," IEEE Trans. Inform. Theory, vol. 56, no. 4, pp. 1982-2001, Apr. 2010.
-
(2010)
IEEE Trans. Inform. Theory
, vol.56
, Issue.4
, pp. 1982-2001
-
-
Baraniuk, R.G.1
Cevher, V.2
Duarte, M.F.3
Hegde, C.4
-
9
-
-
84904317424
-
Compressive sensing via nonlocal low-rank regularization
-
W. Dong, G. Shi, X. Li, Y. Ma, and F. Huang, "Compressive sensing via nonlocal low-rank regularization," IEEE Trans. Image Processing, vol. 23, no. 8, pp. 3618-3632, 2014.
-
(2014)
IEEE Trans. Image Processing
, vol.23
, Issue.8
, pp. 3618-3632
-
-
Dong, W.1
Shi, G.2
Li, X.3
Ma, Y.4
Huang, F.5
-
10
-
-
84983567835
-
From denoising to compressed sensing
-
C. A. Metzler, A. Maleki, and R. G. Baraniuk, "From denoising to compressed sensing," IEEE Trans. Inform. Theory, vol. 62, no. 9, pp. 5117-5144, 2016.
-
(2016)
IEEE Trans. Inform. Theory
, vol.62
, Issue.9
, pp. 5117-5144
-
-
Metzler, C.A.1
Maleki, A.2
Baraniuk, R.G.3
-
12
-
-
85034070274
-
-
ArXiv Preprint
-
S. Beygi, S. Jalali, A. Maleki, and U. Mitra, "An efficient algorithm for compression-based compressed sensing," arXiv preprint arXiv:1704.01992, 2017.
-
(2017)
An Efficient Algorithm for Compression-Based Compressed Sensing
-
-
Beygi, S.1
Jalali, S.2
Maleki, A.3
Mitra, U.4
-
13
-
-
84969776710
-
A deep learning approach to structured signal recovery
-
Control, and Computing
-
A. Mousavi, A. B. Patel, and R. G. Baraniuk, "A deep learning approach to structured signal recovery," Proc. Allerton Conf. Communication, Control, and Computing, pp. 1336-1343, 2015.
-
(2015)
Proc. Allerton Conf. Communication
, pp. 1336-1343
-
-
Mousavi, A.1
Patel, A.B.2
Baraniuk, R.G.3
-
14
-
-
84986249771
-
Reconnet: Non-iterative reconstruction of images from compressively sensed measurements
-
K. Kulkarni, S. Lohit, P. Turaga, R. Kerviche, and A. Ashok, "Reconnet: Non-iterative reconstruction of images from compressively sensed measurements," Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 449-458, 2016.
-
(2016)
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition
, pp. 449-458
-
-
Kulkarni, K.1
Lohit, S.2
Turaga, P.3
Kerviche, R.4
Ashok, A.5
-
15
-
-
85023744403
-
Learning to invert: Signal recovery via deep convolutional networks
-
Speech, and Signal Processing (ICASSP)
-
A. Mousavi and R. G. Baraniuk, "Learning to invert: Signal recovery via deep convolutional networks," Proc. IEEE Int. Conf. Acoust., Speech, and Signal Processing (ICASSP), pp. 2272-2276, 2017.
-
(2017)
Proc. IEEE Int. Conf. Acoust.
, pp. 2272-2276
-
-
Mousavi, A.1
Baraniuk, R.G.2
-
17
-
-
79551480483
-
Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion
-
P. Vincent, H. Larochelle, I. Lajoie, Y. Bengio, and P.-A. Manzagol, "Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion," J. Machine Learning Research, vol. 11, pp. 3371-3408, 2010.
-
(2010)
J. Machine Learning Research
, vol.11
, pp. 3371-3408
-
-
Vincent, P.1
Larochelle, H.2
Lajoie, I.3
Bengio, Y.4
Manzagol, P.-A.5
-
18
-
-
84973380162
-
Approximate message passing with restricted boltzmann machine priors
-
E. W. Tramel, A. Drémeau, and F. Krzakala, "Approximate message passing with restricted Boltzmann machine priors," Journal of Statistical Mechanics: Theory and Experiment, vol. 2016, no. 7, p. 073401, 2016.
-
(2016)
Journal of Statistical Mechanics: Theory and Experiment
, vol.2016
, Issue.7
, pp. 073401
-
-
Tramel, E.W.1
Drémeau, A.2
Krzakala, F.3
-
19
-
-
84998694486
-
Inferring sparsity: Compressed sensing using generalized restricted boltzmann machines
-
E. W. Tramel, A. Manoel, F. Caltagirone, M. Gabrié, and F. Krzakala, "Inferring sparsity: Compressed sensing using generalized restricted Boltzmann machines," Proc. IEEE Information Theory Workshop (ITW), pp. 265-269, 2016.
-
(2016)
Proc. IEEE Information Theory Workshop (ITW)
, pp. 265-269
-
-
Tramel, E.W.1
Manoel, A.2
Caltagirone, F.3
Gabrié, M.4
Krzakala, F.5
-
20
-
-
85046993496
-
-
ArXiv Preprint
-
E. W. Tramel, M. Gabrié, A. Manoel, F. Caltagirone, and F. Krzakala, "A deterministic and generalized framework for unsupervised learning with restricted Boltzmann machines," arXiv preprint arXiv:1702.03260, 2017.
-
(2017)
A Deterministic and Generalized Framework for Unsupervised Learning with Restricted Boltzmann Machines
-
-
Tramel, E.W.1
Gabrié, M.2
Manoel, A.3
Caltagirone, F.4
Krzakala, F.5
-
23
-
-
85041921524
-
One network to solve them all-solving linear inverse problems using deep projection models
-
and Pattern Recognition
-
J. Rick Chang, C.-L. Li, B. Poczos, B. Vijaya Kumar, and A. C. Sankaranarayanan, "One network to solve them all-Solving linear inverse problems using deep projection models," Proc. IEEE Int. Conf. Comp. Vision, and Pattern Recognition, pp. 5888-5897, 2017.
-
(2017)
Proc. IEEE Int. Conf. Comp. Vision
, pp. 5888-5897
-
-
Rick Chang, J.1
Li, C.-L.2
Poczos, B.3
Vijaya Kumar, B.4
Sankaranarayanan, A.C.5
-
25
-
-
84964680324
-
Learning optimal nonlinearities for iterative thresholding algorithms
-
U. S. Kamilov and H. Mansour, "Learning optimal nonlinearities for iterative thresholding algorithms," IEEE Signal Process. Lett., vol. 23, no. 5, pp. 747-751, 2016.
-
(2016)
IEEE Signal Process. Lett.
, vol.23
, Issue.5
, pp. 747-751
-
-
Kamilov, U.S.1
Mansour, H.2
-
27
-
-
85018917190
-
Deep ADMM-net for compressive sensing MRI
-
Y. Yang, J. Sun, H. Li, and Z. Xu, "Deep ADMM-net for compressive sensing MRI," Proc. Adv. in Neural Processing Systems (NIPS), vol. 29, pp. 10-18, 2016.
-
(2016)
Proc. Adv. in Neural Processing Systems (NIPS)
, vol.29
, pp. 10-18
-
-
Yang, Y.1
Sun, J.2
Li, H.3
Xu, Z.4
-
29
-
-
85017397082
-
Bilevel sparse models for polyphonic music transcription
-
T. B. Yakar, P. Sprechmann, R. Litman, A. M. Bronstein, and G. Sapiro, "Bilevel sparse models for polyphonic music transcription." ISMIR, pp. 65-70, 2013.
-
(2013)
ISMIR
, pp. 65-70
-
-
Yakar, T.B.1
Sprechmann, P.2
Litman, R.3
Bronstein, A.M.4
Sapiro, G.5
-
30
-
-
34547760736
-
Image denoising by sparse 3-d transform-domain collaborative filtering
-
Aug.
-
K. Dabov, A. Foi, V. Katkovnik, and K. Egiazarian, "Image denoising by sparse 3-d transform-domain collaborative filtering," IEEE Trans. Image Processing, vol. 16, no. 8, pp. 2080-2095, Aug. 2007.
-
(2007)
IEEE Trans. Image Processing
, vol.16
, Issue.8
, pp. 2080-2095
-
-
Dabov, K.1
Foi, A.2
Katkovnik, V.3
Egiazarian, K.4
-
31
-
-
84897731193
-
Plug-and-play priors for model based reconstruction
-
S. V. Venkatakrishnan, C. A. Bouman, and B. Wohlberg, "Plug-and-play priors for model based reconstruction," Proc. Global Conf. on Signal and Inform. Processing (GlobalSIP), pp. 945-948, 2013.
-
(2013)
Proc. Global Conf. on Signal and Inform. Processing (GlobalSIP)
, pp. 945-948
-
-
Venkatakrishnan, S.V.1
Bouman, C.A.2
Wohlberg, B.3
-
32
-
-
84919754597
-
What regularized auto-encoders learn from the data-generating distribution
-
G. Alain and Y. Bengio, "What regularized auto-encoders learn from the data-generating distribution," J. Machine Learning Research, vol. 15, no. 1, pp. 3563-3593, 2014.
-
(2014)
J. Machine Learning Research
, vol.15
, Issue.1
, pp. 3563-3593
-
-
Alain, G.1
Bengio, Y.2
-
33
-
-
85081923574
-
Amortised map inference for image super-resolution
-
C. K. Sønderby, J. Caballero, L. Theis, W. Shi, and F. Huszár, "Amortised map inference for image super-resolution," Proc. Int. Conf. on Learning Representations (ICLR), 2017.
-
(2017)
Proc. Int. Conf. on Learning Representations (ICLR)
-
-
Sønderby, C.K.1
Caballero, J.2
Theis, L.3
Shi, W.4
Huszár, F.5
-
34
-
-
84996241537
-
Solution of 'Solvable model of a spin glass'
-
D. J. Thouless, P. W. Anderson, and R. G. Palmer, "Solution of 'Solvable model of a spin glass'," Philos. Mag., vol. 35, no. 3, pp. 593-601, 1977.
-
(1977)
Philos. Mag.
, vol.35
, Issue.3
, pp. 593-601
-
-
Thouless, D.J.1
Anderson, P.W.2
Palmer, R.G.3
-
37
-
-
50549090016
-
Monte-Carlo sure: A black-box optimization of regularization parameters for general denoising algorithms
-
S. Ramani, T. Blu, and M. Unser, "Monte-Carlo sure: A black-box optimization of regularization parameters for general denoising algorithms," IEEE Trans. Image Processing, pp. 1540-1554, 2008.
-
(2008)
IEEE Trans. Image Processing
, pp. 1540-1554
-
-
Ramani, S.1
Blu, T.2
Unser, M.3
-
38
-
-
84866679588
-
Image denoising: Can plain neural networks compete with BM3D?
-
and Pattern Recognition
-
H. C. Burger, C. J. Schuler, and S. Harmeling, "Image denoising: Can plain neural networks compete with BM3D?" Proc. IEEE Int. Conf. Comp. Vision, and Pattern Recognition, pp. 2392-2399, 2012.
-
(2012)
Proc. IEEE Int. Conf. Comp. Vision
, pp. 2392-2399
-
-
Burger, H.C.1
Schuler, C.J.2
Harmeling, S.3
-
39
-
-
85021724055
-
Beyond a Gaussian denoiser: Residual learning of deep CNN for image denoising
-
K. Zhang, W. Zuo, Y. Chen, D. Meng, and L. Zhang, "Beyond a Gaussian denoiser: Residual learning of deep CNN for image denoising," IEEE Trans. Image Processing, 2017.
-
(2017)
IEEE Trans. Image Processing
-
-
Zhang, K.1
Zuo, W.2
Chen, Y.3
Meng, D.4
Zhang, L.5
-
40
-
-
84876231242
-
Imagenet classification with deep convolutional neural networks
-
A. Krizhevsky, I. Sutskever, and G. E. Hinton, "Imagenet classification with deep convolutional neural networks," Proc. Adv. in Neural Processing Systems (NIPS), pp. 1097-1105, 2012.
-
(2012)
Proc. Adv. in Neural Processing Systems (NIPS)
, pp. 1097-1105
-
-
Krizhevsky, A.1
Sutskever, I.2
Hinton, G.E.3
-
42
-
-
84986274465
-
Deep residual learning for image recognition
-
and Pattern Recognition
-
K. He, X. Zhang, S. Ren, and J. Sun, "Deep residual learning for image recognition," Proc. IEEE Int. Conf. Comp. Vision, and Pattern Recognition, pp. 770-778, 2016.
-
(2016)
Proc. IEEE Int. Conf. Comp. Vision
, pp. 770-778
-
-
He, K.1
Zhang, X.2
Ren, S.3
Sun, J.4
-
43
-
-
0027274189
-
Neural network constructive algorithms: Trading generalization for learning efficiency?
-
F. J. Śmieja, "Neural network constructive algorithms: Trading generalization for learning efficiency?" Circuits, Systems, and Signal Processing, vol. 12, no. 2, pp. 331-374, 1993.
-
(1993)
Circuits, Systems, and Signal Processing
, vol.12
, Issue.2
, pp. 331-374
-
-
Śmieja, F.J.1
-
44
-
-
79251496987
-
The dynamics of message passing on dense graphs, with applications to compressed sensing
-
M. Bayati and A. Montanari, "The dynamics of message passing on dense graphs, with applications to compressed sensing," IEEE Trans. Inform. Theory, vol. 57, no. 2, pp. 764-785, 2011.
-
(2011)
IEEE Trans. Inform. Theory
, vol.57
, Issue.2
, pp. 764-785
-
-
Bayati, M.1
Montanari, A.2
-
45
-
-
85047004943
-
-
ArXiv Preprint
-
I. Gulrajani, F. Ahmed, M. Arjovsky, V. Dumoulin, and A. Courville, "Improved training of Wasserstein GANs," arXiv preprint arXiv:1704.00028, 2017.
-
(2017)
Improved Training of Wasserstein GANs
-
-
Gulrajani, I.1
Ahmed, F.2
Arjovsky, M.3
Dumoulin, V.4
Courville, A.5
-
46
-
-
0034850577
-
A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics
-
July
-
D. Martin, C. Fowlkes, D. Tal, and J. Malik, "A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics," Proc. Int. Conf. Computer Vision, vol. 2, pp. 416-423, July 2001.
-
(2001)
Proc. Int. Conf. Computer Vision
, vol.2
, pp. 416-423
-
-
Martin, D.1
Fowlkes, C.2
Tal, D.3
Malik, J.4
-
49
-
-
84920061457
-
Phase retrieval from coded diffraction patterns
-
E. J. Candes, X. Li, and M. Soltanolkotabi, "Phase retrieval from coded diffraction patterns," Appl. Comput. Harmon. Anal., vol. 39, no. 2, pp. 277-299, 2015.
-
(2015)
Appl. Comput. Harmon. Anal.
, vol.39
, Issue.2
, pp. 277-299
-
-
Candes, E.J.1
Li, X.2
Soltanolkotabi, M.3
|