Bilinear Compressed Sensing

Abstract

The theory of compressed sensing (CS) has shown that a substantial reduction in sampling and storage complexity can be achieved in many relevant linear and non–adaptive estimation problems. Recent theoretical developments have also put the analysis of a whole range of practical non-linear problems within reach. Examples include blind decoding of wireless signals under channel uncertainties, recovery of images from fuzzy snapshots without precise knowledge of the blurring kernel, or more general model uncertainties in conventional CS. The unifying feature of these tasks is that the signal is accessible only through an uncalibrated system, whose description is partially unknown at the time of measurement. Mathematically, one set of parameters (the channel, the kernel, the sensing matrix) is coupled in a multiplicative way to the signal – giving rise to an inherent emph{bilinear structure}. While in conventional CS such model uncertainties inevitably degrade the quality of the recovery, the novel approach is to combine bilinearity and compressibility in order to simultaneously estimate both the signal and the model parameters.

The theory of bilinear CS is only at its beginnings, but has recently garnered a significant amount of attention and is developing rapidly. (Because it unites and extends the first two structural assumptions considered in the CS community – sparsity and low-rank – it is sometimes refered to as emph{compressed sensing 3.0}). While we believe that engineering applications are within reach over the duration of the Priority Program, considerable mathematical problems remain to be addressed. We have therefore chosen a team of three principal investigators who contribute the necessary diverse set of theoretical and practical expertise. Together, we will work towards a comprehensive theory for bilinear CS. On the one hand, we will study, in an abstract context, recovery properties for random subsampling of bilinear maps, as well as bilinear maps of vectors under random subspace conditions. On the other hand, we will work to develop adapted techniques for specific applications, focusing on wireless communication, but also touching on imaging and spectroscopy.

Cosip (SPP1798 Priority Program)

Bilinear Compressed Sensing Webpage at SPP1798 Priority Program

Related Publications

  1. Alexander Fengler, Saeid Haghighatshoar, Peter Jung and Giuseppe Caire, “Non-Bayesian Activity Detection, Large-Scale Fading Coefficient Estimation, and Unsourced Random Access With a Massive MIMO Receiver,” IEEE Transactions on Information Theory, vol. 67, no. 5, pp. 2925-2951, may 2021.
    [BibTeX] [URL]

    @article{Fengler:TIT:Bayesian:2021,
      author = {Fengler, Alexander and Haghighatshoar, Saeid and Jung, Peter and Caire, Giuseppe},
      title = {Non-Bayesian Activity Detection, Large-Scale Fading Coefficient Estimation, and Unsourced Random Access With a Massive MIMO Receiver},
      journal = {IEEE Transactions on Information Theory},
      year = {2021},
      volume = {67},
      number = {5},
      pages = {2925--2951},
      url = {http://arxiv.org/abs/1910.11266 https://ieeexplore.ieee.org/document/9374476/},
      doi = {http://doi.org/10.1109/TIT.2021.3065291}
    }
    
  2. Hendrik Bernd Petersen, Shankar Agarwal, Peter Jung and Bubacarr Bah, “Improving the Reliability of Pooled Testing with Combinatorial Decoding and Compressed Sensing,” in 55th Annual Conference on Information Sciences and Systems (CISS), 2021.
    [BibTeX]

    @inproceedings{Petersen:ciss21,
      author = {Petersen, Hendrik Bernd and Agarwal, Shankar and Jung, Peter and Bah, Bubacarr},
      title = {Improving the Reliability of Pooled Testing with Combinatorial Decoding and Compressed Sensing},
      booktitle = {55th Annual Conference on Information Sciences and Systems (CISS)},
      year = {2021}
    }
    
  3. Robert Beinert, Peter Jung, Gabriele Steidl and Tom Szollmann, “Super-Resolution for Doubly-Dispersive Channel Estimation,” jan 2021.
    [BibTeX] [URL]

    @article{Beinert2021,
      author = {Beinert, Robert and Jung, Peter and Steidl, Gabriele and Szollmann, Tom},
      title = {Super-Resolution for Doubly-Dispersive Channel Estimation},
      year = {2021},
      url = {http://arxiv.org/abs/2101.11544}
    }
    
  4. Hendrik Bernd Petersen, Bubacarr Bah and Peter Jung, “Efficient Noise-Blind $1$-Regression of Nonnegative Compressible Signals,” to appear in Frontiers in Applied Mathematics and Statistics, mar 2021.
    [BibTeX] [URL]

    @article{Petersen:nnlad,
      author = {Petersen, Hendrik Bernd and Bah, Bubacarr and Jung, Peter},
      title = {Efficient Noise-Blind $1$-Regression of Nonnegative Compressible Signals},
      journal = {to appear in Frontiers in Applied Mathematics and Statistics},
      year = {2021},
      url = {http://arxiv.org/abs/2003.13092}
    }
    
  5. Martin Reiche and Peter Jung, “DeepInit Phase Retrieval,” jul 2020.
    [BibTeX] [URL]

    @article{Reiche:deepinit:2020,
      author = {Reiche, Martin and Jung, Peter},
      title = {DeepInit Phase Retrieval},
      year = {2020},
      url = {http://arxiv.org/abs/2007.08214}
    }
    
  6. Philipp Walk, Peter Jung, Babak Hassibi and Hamid Jafarkhani, “MOCZ for Blind Short-Packet Communication: Practical Aspects,” IEEE Transactions on Wireless Communications, vol. 19, no. 10, pp. 6675-6692, feb 2020.
    [BibTeX] [URL]

    @article{Walk:TWC:MOCZ:practicalaspects,
      author = {Walk, Philipp and Jung, Peter and Hassibi, Babak and Jafarkhani, Hamid},
      title = {MOCZ for Blind Short-Packet Communication: Practical Aspects},
      journal = {IEEE Transactions on Wireless Communications},
      year = {2020},
      volume = {19},
      number = {10},
      pages = {6675--6692},
      url = {https://ieeexplore.ieee.org/document/9141440/},
      doi = {http://doi.org/10.1109/twc.2020.3004588}
    }
    
  7. Martin Genzel and Peter Jung, “Recovering Structured Data from Superimposed Non-Linear Measurements,” IEEE Transactions on Information Theory, vol. 66, no. 1, pp. 453-477, jan 2020.
    [BibTeX] [URL]

    @article{Genzel:TIT:2019,
      author = {Genzel, Martin and Jung, Peter},
      title = {Recovering Structured Data from Superimposed Non-Linear Measurements},
      journal = {IEEE Transactions on Information Theory},
      year = {2020},
      volume = {66},
      number = {1},
      pages = {453--477},
      url = {http://arxiv.org/abs/1708.07451 https://ieeexplore.ieee.org/document/8784241/},
      doi = {http://doi.org/10.1109/TIT.2019.2932426}
    }
    
  8. Fabian Jaensch and Peter Jung, “Robust Recovery of Sparse Nonnegative Weights from Mixtures of Positive-Semidefinite Matrices,” mar 2020.
    [BibTeX] [URL]

    @article{Jaensch2020,
      author = {Jaensch, Fabian and Jung, Peter},
      title = {Robust Recovery of Sparse Nonnegative Weights from Mixtures of Positive-Semidefinite Matrices},
      year = {2020},
      url = {http://arxiv.org/abs/2003.12005}
    }
    
  9. Hendrik Bernd Petersen and Peter Jung, “Robust Instance-Optimal Recovery of Sparse Signals at Unknown Noise Levels,” aug 2020.
    [BibTeX] [URL]

    @article{Petersen:slasso,
      author = {Petersen, Hendrik Bernd and Jung, Peter},
      title = {Robust Instance-Optimal Recovery of Sparse Signals at Unknown Noise Levels},
      year = {2020},
      url = {http://arxiv.org/abs/2008.08385}
    }
    
  10. Hendrik Bernd Petersen, Bubacarr Bah and Peter Jung, “Practical High-Throughput, Non-Adaptive and Noise-Robust SARS-CoV-2 Testing,” jul 2020.
    [BibTeX] [URL]

    @article{Petersen:covidtesting,
      author = {Petersen, Hendrik Bernd and Bah, Bubacarr and Jung, Peter},
      title = {Practical High-Throughput, Non-Adaptive and Noise-Robust SARS-CoV-2 Testing},
      year = {2020},
      url = {http://arxiv.org/abs/2007.09171}
    }
    
  11. Yonatan Shadmi, Peter Jung and Giuseppe Caire, “Sparse Non-Negative Recovery from Biased Subgaussian Measurements using NNLS,” jan 2019.
    [BibTeX] [URL]

    @article{Shadmi2019,
      author = {Shadmi, Yonatan and Jung, Peter and Caire, Giuseppe},
      title = {Sparse Non-Negative Recovery from Biased Subgaussian Measurements using NNLS},
      year = {2019},
      url = {http://arxiv.org/abs/1901.05727}
    }
    
  12. Martin Kliesch, Stanislaw J. Szarek and Peter Jung, “Simultaneous Structures in Convex Signal Recovery—Revisiting the Convex Combination of Norms,” Frontiers in Applied Mathematics and Statistics, vol. 5, may 2019.
    [BibTeX] [URL]

    @article{Kliesch2019,
      author = {Kliesch, Martin and Szarek, Stanislaw J. and Jung, Peter},
      title = {Simultaneous Structures in Convex Signal Recovery—Revisiting the Convex Combination of Norms},
      journal = {Frontiers in Applied Mathematics and Statistics},
      year = {2019},
      volume = {5},
      url = {http://arxiv.org/abs/1904.07893 https://www.frontiersin.org/article/10.3389/fams.2019.00023/full},
      doi = {http://doi.org/10.3389/fams.2019.00023}
    }
    
  13. Alexander Fengler, Peter Jung and Giuseppe Caire, “SPARCs for Unsourced Random Access,” jan 2019.
    [BibTeX] [URL]

    @article{Fengler2019a,
      author = {Fengler, Alexander and Jung, Peter and Caire, Giuseppe},
      title = {SPARCs for Unsourced Random Access},
      year = {2019},
      url = {http://arxiv.org/abs/1901.06234}
    }
    
  14. Peter Jung, Richard Kueng and Dustin G. Mixon, “Derandomizing Compressed Sensing With Combinatorial Design,” Frontiers in Applied Mathematics and Statistics, vol. 5, jun 2019.
    [BibTeX] [URL]

    @article{Jung:frontiers18,
      author = {Jung, Peter and Kueng, Richard and Mixon, Dustin G.},
      title = {Derandomizing Compressed Sensing With Combinatorial Design},
      journal = {Frontiers in Applied Mathematics and Statistics},
      year = {2019},
      volume = {5},
      url = {https://www.frontiersin.org/article/10.3389/fams.2019.00026/full},
      doi = {http://doi.org/10.3389/fams.2019.00026}
    }
    
  15. A. Fengler, P. Jung and G. Caire, “SPARCs and AMP for Unsourced Random Access,” in IEEE Int. Symposium on Information Theory (ISIT), 2019.
    [BibTeX]

    @inproceedings{Fengler:isit19,
      author = {Fengler, A. and Jung, P. and Caire, G.},
      title = {SPARCs and AMP for Unsourced Random Access},
      booktitle = {IEEE Int. Symposium on Information Theory (ISIT)},
      year = {2019}
    }
    
  16. Philipp Walk, Peter Jung and Babak Hassibi, “MOCZ for Blind Short-Packet Communication: Basic Principles,” IEEE Transactions on Wireless Communications, vol. 18, no. 11, pp. 5080-5097, nov 2019.
    [BibTeX] [URL]

    @article{Walk:TWC:MOCZ:basicprinciples,
      author = {Walk, Philipp and Jung, Peter and Hassibi, Babak},
      title = {MOCZ for Blind Short-Packet Communication: Basic Principles},
      journal = {IEEE Transactions on Wireless Communications},
      year = {2019},
      volume = {18},
      number = {11},
      pages = {5080--5097},
      url = {https://ieeexplore.ieee.org/document/8792390/},
      doi = {http://doi.org/10.1109/TWC.2019.2932668}
    }
    
  17. Alexander Fengler and Peter Jung, “On the Restricted Isometry Property of Centered Self Khatri-Rao Products,” may 2019.
    [BibTeX] [URL]

    @article{Fengler:krrip:2019,
      author = {Fengler, Alexander and Jung, Peter},
      title = {On the Restricted Isometry Property of Centered Self Khatri-Rao Products},
      year = {2019},
      url = {http://arxiv.org/abs/1905.09245}
    }
    
  18. Alexander Fengler, Giuseppe Caire, Peter Jung and Saeid Haghighatshoar, “Massive MIMO Unsourced Random Access,” jan 2019.
    [BibTeX] [URL]

    @article{Fengler2019,
      author = {Fengler, Alexander and Caire, Giuseppe and Jung, Peter and Haghighatshoar, Saeid},
      title = {Massive MIMO Unsourced Random Access},
      year = {2019},
      url = {http://arxiv.org/abs/1901.00828}
    }
    
  19. Y. Shadmi, P. Jung and G. Caire, “Sparse Non-Negative Recovery from Shifted Symmetric Subgaussian Measurements using NNLS,” in IEEE Int. Symposium on Information Theory (ISIT), 2019.
    [BibTeX]

    @inproceedings{Shadmi:isit19,
      author = {Shadmi, Y. and Jung, P. and Caire, G.},
      title = {Sparse Non-Negative Recovery from Shifted Symmetric Subgaussian Measurements using NNLS},
      booktitle = {IEEE Int. Symposium on Information Theory (ISIT)},
      year = {2019}
    }
    
  20. Alexander Fengler, Saeid Haghighatshoar, Peter Jung and Giuseppe Caire, “Grant-Free Massive Random Access with a Massive MIMO Receiver,” in Conference Record - Asilomar Conference on Signals, Systems and Computers, vol. 2019-Novem, pp. 23-30, nov 2019.
    [BibTeX] [URL]

    @inproceedings{fengler:asilomar19,
      author = {Fengler, Alexander and Haghighatshoar, Saeid and Jung, Peter and Caire, Giuseppe},
      title = {Grant-Free Massive Random Access with a Massive MIMO Receiver},
      booktitle = {Conference Record - Asilomar Conference on Signals, Systems and Computers},
      year = {2019},
      volume = {2019-Novem},
      pages = {23--30},
      url = {http://arxiv.org/abs/1912.01459 https://ieeexplore.ieee.org/document/9049039},
      doi = {http://doi.org/10.1109/IEEECONF44664.2019.9049039}
    }
    
  21. Martin Burger, Janic Föcke, Lukas Nickel, Peter Jung and Sven Augustin, “Reconstruction Methods in THz Single-Pixel Imaging,” pp. 263-290, mar 2019.
    [BibTeX] [URL]

    @incollection{burger:csa2017,
      author = {Burger, Martin and Föcke, Janic and Nickel, Lukas and Jung, Peter and Augustin, Sven},
      title = {Reconstruction Methods in THz Single-Pixel Imaging},
      booktitle = {Compressed Sensing and Applications},
      publisher = {Springer},
      year = {2019},
      pages = {263--290},
      url = {http://arxiv.org/abs/1903.08893 https://rd.springer.com/chapter/10.1007/978-3-319-73074-5_9 http://link.springer.com/10.1007/978-3-319-73074-5_9},
      doi = {http://doi.org/10.1007/978-3-319-73074-5_9}
    }
    
  22. Peter Jung and Martin Genzel, “Blind Sparse Recovery Using Imperfect Sensor Networks,” in 2018 IEEE Statistical Signal Processing Workshop, SSP 2018, pp. 433-437, 2018.
    [BibTeX] [URL]

    @inproceedings{Jung:ssp18,
      author = {Jung, Peter and Genzel, Martin},
      title = {Blind Sparse Recovery Using Imperfect Sensor Networks},
      booktitle = {2018 IEEE Statistical Signal Processing Workshop, SSP 2018},
      year = {2018},
      pages = {433--437},
      url = {https://ieeexplore.ieee.org/document/8450719},
      doi = {http://doi.org/10.1109/SSP.2018.8450719}
    }
    
  23. Peter Jung, Felix Krahmer and Dominik Stoeger, “Blind Demixing and Deconvolution at Near-Optimal Rate,” IEEE Transactions on Information Theory, vol. 64, no. 2, pp. 704-727, feb 2018.
    [BibTeX] [URL]

    @article{Jung:TIT:2017,
      author = {Jung, Peter and Krahmer, Felix and Stoeger, Dominik},
      title = {Blind Demixing and Deconvolution at Near-Optimal Rate},
      journal = {IEEE Transactions on Information Theory},
      year = {2018},
      volume = {64},
      number = {2},
      pages = {704--727},
      url = {http://arxiv.org/abs/1704.04178 http://ieeexplore.ieee.org/document/8240933/},
      doi = {http://doi.org/10.1109/TIT.2017.2784481}
    }
    
  24. Philipp Walk, Peter Jung and Babak Hassibi, “Noncoherent Short-Packet Communication via Modulation on Conjugated Zeros,” may 2018.
    [BibTeX] [URL]

    @article{Walk:mocz:preprint,
      author = {Walk, Philipp and Jung, Peter and Hassibi, Babak},
      title = {Noncoherent Short-Packet Communication via Modulation on Conjugated Zeros},
      year = {2018},
      url = {http://arxiv.org/abs/1805.07876}
    }
    
  25. Sven Augustin, Sven Frohmann, Peter Jung and Heinz-Wilhelm Hübers, “Mask Responses for Single-Pixel Terahertz Imaging,” Scientific Reports, vol. 8, no. 1, pp. 4886, dec 2018.
    [BibTeX] [URL]

    @article{Augustin:srep18,
      author = {Augustin, Sven and Frohmann, Sven and Jung, Peter and Hübers, Heinz-Wilhelm},
      title = {Mask Responses for Single-Pixel Terahertz Imaging},
      journal = {Scientific Reports},
      year = {2018},
      volume = {8},
      number = {1},
      pages = {4886},
      url = {http://www.nature.com/articles/s41598-018-23313-6},
      doi = {http://doi.org/10.1038/s41598-018-23313-6}
    }
    
  26. O. Musa, P. Jung and N. Goertz, “Generalized Approximate Message Passing for Unlimited Sampling of Sparse Signals,” in GlobalSIP, 2018.
    [BibTeX] [URL]

    @inproceedings{Musa:globalsip18,
      author = {Musa, O. and Jung, P. and Goertz, N.},
      title = {Generalized Approximate Message Passing for Unlimited Sampling of Sparse Signals},
      booktitle = {GlobalSIP},
      year = {2018},
      url = {https://arxiv.org/abs/1807.03182}
    }
    
  27. Saeid Haghighatshoar, Peter Jung and Giuseppe Caire, “A New Scaling Law for Activity Detection in Massive MIMO Systems,” mar 2018.
    [BibTeX] [URL]

    @article{Haghighatshoar2018,
      author = {Haghighatshoar, Saeid and Jung, Peter and Caire, Giuseppe},
      title = {A New Scaling Law for Activity Detection in Massive MIMO Systems},
      year = {2018},
      url = {http://arxiv.org/abs/1803.02288}
    }
    
  28. Saeid Haghighatshoar, Peter Jung and Giuseppe Caire, “Improved Scaling Law for Activity Detection in Massive MIMO Systems,” in 2018 IEEE International Symposium on Information Theory (ISIT), pp. 381-385, jun 2018.
    [BibTeX] [URL]

    @inproceedings{Hag:isit18,
      author = {Haghighatshoar, Saeid and Jung, Peter and Caire, Giuseppe},
      title = {Improved Scaling Law for Activity Detection in Massive MIMO Systems},
      booktitle = {2018 IEEE International Symposium on Information Theory (ISIT)},
      publisher = {IEEE},
      year = {2018},
      pages = {381--385},
      url = {https://ieeexplore.ieee.org/document/8437359/},
      doi = {http://doi.org/10.1109/ISIT.2018.8437359}
    }
    
  29. Martin Genzel and Peter Jung, “Sparse Recovery From Superimposed Non-Linear Measurements,” in GAMM2018, 2018.
    [BibTeX]

    @inproceedings{Genzel:gamm18,
      author = {Genzel, Martin and Jung, Peter},
      title = {Sparse Recovery From Superimposed Non-Linear Measurements},
      booktitle = {GAMM2018},
      year = {2018}
    }
    
  30. Richard Kueng and Peter Jung, “Robust Nonnegative Sparse Recovery and the Nullspace Property of 0/1 Measurements,” IEEE Transactions on Information Theory, vol. 64, no. 2, pp. 689-703, feb 2018.
    [BibTeX] [URL]

    @article{kueng:16:nnls,
      author = {Kueng, Richard and Jung, Peter},
      title = {Robust Nonnegative Sparse Recovery and the Nullspace Property of 0/1 Measurements},
      journal = {IEEE Transactions on Information Theory},
      year = {2018},
      volume = {64},
      number = {2},
      pages = {689--703},
      url = {http://arxiv.org/abs/1603.07997 http://ieeexplore.ieee.org/document/8022909/},
      doi = {http://doi.org/10.1109/TIT.2017.2746620}
    }
    
  31. Carsten Herrmann, Yun Lu, Christian Scheunert and Peter Jung, “Improving Robustness for Anisotropic Sparse Recovery using Matrix Extensions,” in Workshop on Smart Antennas (WSA), 2018.
    [BibTeX]

    @inproceedings{herrmann:wsa18,
      author = {Herrmann, Carsten and Lu, Yun and Scheunert, Christian and Jung, Peter},
      title = {Improving Robustness for Anisotropic Sparse Recovery using Matrix Extensions},
      booktitle = {Workshop on Smart Antennas (WSA)},
      year = {2018}
    }
    
  32. P. Jung, P Walk, G.E. Pfander and B. Hassibi, “Blind Deconvolution and Polynomial Factorization,” in BASP Frontiers, no. 1, pp. 1, 2017.
    [BibTeX] [URL]

    @inproceedings{jung:basp17,
      author = {Jung, P. and Walk, P and Pfander, G.E. and Hassibi, B.},
      title = {Blind Deconvolution and Polynomial Factorization},
      booktitle = {BASP Frontiers},
      year = {2017},
      number = {1},
      pages = {1},
      url = {http://www.user.tu-berlin.de/peter.jung/papers/Jung-BASP17-Poster-Blind_Deconvolution_and_Polynomial_Factorization.pdf}
    }
    
  33. D. Stoeger, P. Jung and F. Krahmer, “Blind demixing and deconvolution with noisy data at near optimal rate,” in SPIE, 2017.
    [BibTeX]

    @inproceedings{stoeger:spie17,
      author = {Stoeger, D. and Jung, P. and Krahmer, F.},
      title = {Blind demixing and deconvolution with noisy data at near optimal rate},
      booktitle = {SPIE},
      year = {2017}
    }
    
  34. R. Kueng and P. Jung, “Convex signal reconstruction with positivity constraints,” in BASP Frontiers, 2017.
    [BibTeX]

    @inproceedings{kueng:basp17,
      author = {Kueng, R. and Jung, P.},
      title = {Convex signal reconstruction with positivity constraints},
      booktitle = {BASP Frontiers},
      year = {2017}
    }
    
  35. P. Walk, P. Jung and B. Hassibi, “Blind Signal Transmission Using Huffman Sequences,” in Information Theory and Applications Workshop, 2017.
    [BibTeX] [URL]

    @inproceedings{Walk:ita2017,
      author = {Walk, P. and Jung, P. and Hassibi, B.},
      title = {Blind Signal Transmission Using Huffman Sequences},
      booktitle = {Information Theory and Applications Workshop},
      year = {2017},
      url = {http://ita.ucsd.edu/workshop/17/files/abstract/abstract_4697.txt}
    }
    
  36. S. Augustin, Z. Szollmann, P. Jung and H.W. Hübers, “Breaking Imaging Limits using Dithering Masks in 0.35 Terahertz Single-Pixel Imaging,” 2017.
    [BibTeX] [URL]

    @inproceedings{Augustin:icassp18,
      author = {Augustin, S. and Szollmann, Z. and Jung, P. and Hübers, H.W.},
      title = {Breaking Imaging Limits using Dithering Masks in 0.35 Terahertz Single-Pixel Imaging},
      year = {2017},
      url = {https://arxiv.org/abs/1711.02995}
    }
    
  37. D. Stoeger, P. Jung and F. Krahmer, “Blind Demixing and Deconvolution with Noisy Data: Near-optimal Rate,” in 21st International ITG Workshop on Smart Antenna, 2017.
    [BibTeX]

    @inproceedings{Stoeger:wsa17,
      author = {Stoeger, D. and Jung, P. and Krahmer, F.},
      title = {Blind Demixing and Deconvolution with Noisy Data: Near-optimal Rate},
      booktitle = {21st International ITG Workshop on Smart Antenna},
      year = {2017}
    }
    
  38. M. Genzel and P. Jung, “Blind Sparse Recovery From Superimposed Non-Linear Sensor Measurements,” in Sampling Theory and Applications, 12th International Conference, 2017.
    [BibTeX] [URL]

    @inproceedings{genzel:sampta17,
      author = {Genzel, M. and Jung, P.},
      title = {Blind Sparse Recovery From Superimposed Non-Linear Sensor Measurements},
      booktitle = {Sampling Theory and Applications, 12th International Conference},
      year = {2017},
      url = {http://www.user.tu-berlin.de/peter.jung/papers/Genzel-Sampta17-Blind_Sparse_Recovery_From_Superimposed_Nonlinear_Sensor_Measurements.pdf},
      doi = {http://doi.org/10.1109/SAMPTA.2017.8024352}
    }
    
  39. Philipp Walk, Peter Jung, Götz E. Pfander and Babak Hassibi, “Blind Deconvolution with Additional Autocorrelations via Convex Programs,” jan 2017.
    [BibTeX] [URL]

    @article{Walk:asilomar16:arxiv,
      author = {Walk, Philipp and Jung, Peter and Pfander, Götz E. and Hassibi, Babak},
      title = {Blind Deconvolution with Additional Autocorrelations via Convex Programs},
      year = {2017},
      url = {http://arxiv.org/abs/1701.04890}
    }
    
  40. M. Genzel and P. Jung, “Sparse Recovery From Superimposed Non-Linear Sensor Measurements,” in SPARS17, 2017.
    [BibTeX] [URL]

    @inproceedings{Genzel:spars17,
      author = {Genzel, M. and Jung, P.},
      title = {Sparse Recovery From Superimposed Non-Linear Sensor Measurements},
      booktitle = {SPARS17},
      year = {2017},
      url = {http://www.user.tu-berlin.de/peter.jung/papers/Genzel-SPARS17-Sparse_Recovery_From_Superimposed_Non-Linear_Sensor_Measurements.pdf}
    }
    
  41. P. Walk, P. Jung and B. Hassibi, “Constrained Blind Deconvolution using Wirtinger Flow Methods,” in Sampling Theory and Applications, 12th International Conference, 2017.
    [BibTeX]

    @inproceedings{walk:sampta17,
      author = {Walk, P. and Jung, P. and Hassibi, B.},
      title = {Constrained Blind Deconvolution using Wirtinger Flow Methods},
      booktitle = {Sampling Theory and Applications, 12th International Conference},
      year = {2017}
    }
    
  42. R. Kueng and P. Jung, “Robust Nonnegative Sparse Recovery and 0/1-Bernoulli Measurements,” in IEEE Inf. Theory Workshop (ITW), 2016.
    [BibTeX]

    @inproceedings{kueng:itw16,
      author = {Kueng, R. and Jung, P.},
      title = {Robust Nonnegative Sparse Recovery and 0/1-Bernoulli Measurements},
      booktitle = {IEEE Inf. Theory Workshop (ITW)},
      year = {2016}
    }
    
  43. D. Stoeger, P. Jung and F. Krahmer, “Blind deconvolution and Compressed Sensing,” in Cosera 2016, 2016.
    [BibTeX]

    @inproceedings{Stoeger:cosera16,
      author = {Stoeger, D. and Jung, P. and Krahmer, F.},
      title = {Blind deconvolution and Compressed Sensing},
      booktitle = {Cosera 2016},
      year = {2016}
    }
    
  44. P. Walk, P. Jung, G. E. Pfander and B. Hassibi, “Ambiguities of Convolutions with Application to Phase Retrieval Problems,” in Asilomar 2016, invited paper, 2016.
    [BibTeX]

    @inproceedings{walk:asilomar16,
      author = {Walk, P. and Jung, P. and Pfander, G. E. and Hassibi, B.},
      title = {Ambiguities of Convolutions with Application to Phase Retrieval Problems},
      booktitle = {Asilomar 2016, invited paper},
      year = {2016}
    }
    
  45. Yunyang Chang, Peter Jung, Chan Zhou and Slawomir Stanczak, “Block Compressed Sensing Based Distributed Device Detection for M2M Communications,” in preparation, pp. 1-27, sep 2016.
    [BibTeX] [URL]

    @article{Chang2016,
      author = {Chang, Yunyang and Jung, Peter and Zhou, Chan and Stanczak, Slawomir},
      title = {Block Compressed Sensing Based Distributed Device Detection for M2M Communications},
      journal = {in preparation},
      year = {2016},
      pages = {1--27},
      url = {http://arxiv.org/abs/1609.05080}
    }
    
  46. Jakob Geppert, Peter Jung, Felix Krahmer and Dominik Stoeger, “Bilinear Compressed Sensing,” in GAMM2018, .
    [BibTeX]

    @inproceedings{Geppert:gamm18,
      author = {Geppert, Jakob and Jung, Peter and Krahmer, Felix and Stoeger, Dominik},
      title = {Bilinear Compressed Sensing},
      booktitle = {GAMM2018}
    }