Conference

2024

  1. Y. Hu, S. V. V. N. Kothapalli, W. Gan, A. L. Sukstanskii, G. F. Wu, M. Goyal, D. A. Yablonskiy, U. S. Kamilov, “DiffGEPCI: 3D MRI Synthesis from mGRE Signals using 2.5D Diffusion Model,” Proc. Int. Symp. Biomedical Imaging 2024 (ISBI 2024) (Athens, Greece, May 27-30), in press.
    [arXiv:2311.18073]
  2. Y. Hu, M. Delbracio, P. Milanfar, and U. S. Kamilov, “A Restoration Network as an Implicit Prior,” Proc. Int. Conf. Learn. Represent. (ICLR 2024) (Vienna, Austria, May 7-11), in press.
    [Project Page] [arXiv:2310.01391]
  3. J. Hu, W. Gan, Z. Sun, H. An, and U. S. Kamilov, “A Plug-and-Play Image Registration Network,” Proc. Int. Conf. Learn. Represent. (ICLR 2024) (Vienna, Austria, May 7-11), in press.
    [Project Page] [arXiv:2310.04297]
  4. M. Renaud, J. Liu, V. de Bortoli, A. Almansa, and U. S. Kamilov, “Plug-and-Play Posterior Sampling under Mismatched Measurement and Prior Models,” Proc. Int. Conf. Learn. Represent. (ICLR 2024) (Vienna, Austria, May 7-11), in press.
    [Project Page] [arXiv:2310.03546]

2023

  1. W. Gan, S. Shoushtari, Y. Hu, J. Liu, H. An, and U. S. Kamilov, “Block Coordinate Plug-and-Play Methods for Blind Inverse Problems,” Proc. Ann. Conf. Neural Information Processing Systems (NeurIPS 2023) (New Orleans, LA, December 10-December 16).
    [Project Page] [arXiv:2305.12672]
  2. S. Hurault, U. S. Kamilov, A. Leclaire, and N. Papadakis, “Convergent Bregman Plug-and-Play Image Restoration for Poisson Inverse Problems,” Proc. Ann. Conf. Neural Information Processing Systems (NeurIPS 2023) (New Orleans, LA, December 10-December 16).
    [arXiv:2306.03466]
  3. C. Park, S. Shoustari, W. Gan, and U. S. Kamilov, “Convergence of Nonconvex PnP-ADMM With MMSE Denoisers,” Proc. Int. Workshop on Computational Advances in Multi-Sensor Adaptive Process. (CAMSAP 2023) (Los Suenos, Costa Rica, December 10-13), pp. 511-515.
    [Project Page] [doi:10.1109/CAMSAP58249.2023.10403463] [CAMSAP 2023 Student Paper Award finalist]
  4. E. P. Chandler, S. Shoustari, J. Liu, M. S. Asif, and U. S. Kamilov, “Overcoming Distribution Shifts in Plug-And-Play Methods With Test-Time Training,” Proc. Int. Workshop on Computational Advances in Multi-Sensor Adaptive Process. (CAMSAP 2023) (Los Suenos, Costa Rica, December 10-13), pp. 186-190.
    [doi:10.1109/CAMSAP58249.2023.10403502]
  5. J. Liu, R. Anirudh, J. J. Thiagarajan, S. He, K. A. Mohan, U. S. Kamilov, and H. Kim, “DOLCE: A Model-Based Probabilistic Diffusion Framework for Limited-Angle CT Reconstruction,” Proc. IEEE Int. Conf. Comp. Vis. (ICCV 2023) (Paris, France, October 2–6), pp. 10498-10508.
    [Project Page] [cvf] [arXiv:2211.12340]
  6. S. Shoushtari, J. Liu, and U. S. Kamilov, “DOLPH: Diffusion Models for Phase Retrieval,” 57th Asilomar Conf. Signals, Systems, & Computers 2023, (Pacific Grove, CA, October 29-November 1), in press.
    [arXiv:2211.00529]
  7. T. Kerepecky, J. Liu, X. W. Ng, D. W. Piston, U. S. Kamilov, “Dual-Cycle: Self-Supervised Dual-View Fluorescence Microscopy Image Reconstruction using CycleGAN,” Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP 2023) (Rhodes Island, Greece, June 4–10).
    [doi:10.1109/icassp49357.2023.10095386] [arXiv:2209.11729]
  8. J. Hu, S. Shoushtari, Z. Zou, J. Liu, Z. Sun, and U. S. Kamilov, “Robustness of Deep Equilibrium Architectures to Changes in the Measurement Model,” Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP 2023) (Rhodes Island, Greece, June 4–10).
    [doi:10.1109/icassp49357.2023.10096199] [arXiv:2211.00531]
  9. W. Gan, H. Gao, Z. Sun, and U. S. Kamilov, “SINCO: A Novel structural regularizer for image compression using implicit neural representations,” Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP 2023) (Rhodes Island, Greece, June 4–10).
    [doi:10.1109/icassp49357.2023.10095531] [arXiv:2210.14974]
  10. P. E. Boroojeni, W. Gan, J. Liu, Y. Hu, Y. Chen, P. Commean, C. Eldeniz, T. Wang, G. Skolnick, C. Merrill, K. Patel, Hongyu An, and U. S. Kamilov, “Deep Unfolding MR reconstruction – weighting the k-space sampling Density in training Loss (wkDeLo),” Proc. Int. Soc. of Magnetic Resonance in Medicine (ISMRM 2023) (Toronto, Canada, 3-8 June), in press.

2022

  1. J. Liu, X. Xu, W. Gan, S. Shoushtari, and U. S. Kamilov, “Online Deep Equilibrium Learning for Regularization by Denoising,” Proc. Ann. Conf. Neural Information Processing Systems (NeurIPS 2022) (New Orleans, LA, November 28-December 9), in press.
    [Proc. NeurIPS 2022] [arXiv:2205.13051] [Acceptance rate: 2665/10411 = 25.6%]
  2. W. Shangguan, Y. Sun, W. Gan, and U. S. Kamilov, “Learning Cross-Video Neural Representations for High-Quality Frame Interpolation,” Proc. European Conference on Computer Vision (ECCV 2022) (Tel Aviv, Israel, October 23-27), pp. 511-528.
    [Project Page] [doi:10.1007/978-3-031-19784-0_30] [arXiv:2203.00137] [Acceptance rate: 1645/5804 = 28%]
  3. Y. Hu, J. Liu, X. Xu, and U. S. Kamilov, “Monotonically Convergent Regularization by Denoising,” Proc. IEEE Int. Conf. Image Proc. (ICIP 2022) (Bordeaux, France, October 16-19), pp. 426-430.
    [doi:10.1109/icip46576.2022.9897639] [arXiv:2202.04961]
  4. A. H. Al-Shabili, X. Xu, I. Selesnick, and U. S. Kamilov, “Bregman Plug-and-Play Priors,” Proc. IEEE Int. Conf. Image Proc. (ICIP 2022) (Bordeaux, France, October 16-19), pp. 241-245.
    [10.1109/icip46576.2022.9897933] [arXiv:2202.02388]
  5. Z. Zhang, J. Liu, D. Yang, U. S. Kamilov, and G. Hugo, “Deep Learning-Based Motion Compensation for 4D-CBCT Reconstruction,” Ann. Meeting American Association of Physicists in Medicine (AAPM 2022) (Washington, DC, 10-14 July), p. 65461.
    [Best-in-Physics Award in Imaging]
  6. S. Chen, C. Eldeniz, T. J. Fraum, D. Ludwig, W. Gan, U. S. Kamilov, D. Yang, and H. An, “Respiratory Motion Detection and Reconstruction Using CAPTURE and Deep Learning Phase2Phase Network for a 0.35 T MRI-LINAC System,” Ann. Meeting American Association of Physicists in Medicine (AAPM 2022) (Washington, DC, 10-14 July), p. 66527
    [Best-in-Physics Award in Imaging]
  7. S. Chen, W. Gan, C. Eldeniz, U. S. Kamilov, T. J. Fraum, and H. An, “DL-MOTIF: Deep Learning Based Motion Transformation Integrated Forward-Fourier Reconstruction for Free-Breathing Liver DCE-MRI,” Proc. Int. Soc. of Magnetic Resonance in Medicine (ISMRM 2022) (London, UK, 7-12 May), p. 3469.
  8. S. Chen, T. J. Fraum, C. Eldeniz, J. Mhlanga, W. Gan, T. Vahle, U. B. Krishnamurthy, D. Faul, H. M. Gach, M. M. Bankley, U. S. Kamilov, R. Laforest, and H. An, “MR-Assisted PET Respiratory Motion Correction Using Deep-Learning Based Short-Scan Motion Fields,” Proc. Int. Soc. of Magnetic Resonance in Medicine (ISMRM 2022) (London, UK, 7-12 May), p. 128.

2021

  1. J. Liu, S. Asif, B. Wohlberg, and U. S. Kamilov, “Recovery Analysis for Plug-and-Play Priors using the Restricted Eigenvalue Condition,” Proc. Ann. Conf. Neural Information Processing Systems (NeurIPS 2021) (December 6-14), pp. 5921-5933.
    [OpenReview] [NeurIPS] [arXiv:2106.03668] [Acceptance rate: 2371/9122 = 26%]
  2. M. Xie, J. Liu, Y. Sun, B. Wohlberg, and U. S. Kamilov, “Joint Reconstruction and Calibration using Regularization by Denoising,” Proc. IEEE Int. Conf. Comp. Vis. Workshops (ICCVW 2021) (Oct 11-17), pp. 4028-4037.
    [10.1109/iccvw54120.2021.00448] [cvf] [arXiv:2011.13391]
  3. W. Gan, Y. Hu, C. Eldeniz, J. Liu, Y. Chen, H. An, and U. S. Kamilov, “SS-JIRCS: Self-Supervised Joint Image Reconstruction and Coil Sensitivity Calibration in Parallel MRI without Ground Truth,” Proc. IEEE Int. Conf. Comp. Vis. Workshops (ICCVW 2021) (Oct 11-17), pp. 4048-4056.
    [10.1109/iccvw54120.2021.00450] [cvf]
  4. J. Liu, Y. Sun, W. Gan, X. Xu, B. Wohlberg, and U. S. Kamilov, “Stochastic Deep Unfolding for Imaging Inverse Problems,” Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP 2021) (Toronto, Canada, June 6-11), pp. 1395-1399.
    [doi:10.1109/icassp39728.2021.9414332]
  5. W. Gan, Y. Sun, C. Eldeniz, J. Liu, H. An, and U. S. Kamilov, “Deep image reconstruction for MRI using unregistered measurement pairs without ground truth,” Proc. Int. Soc. of Magnetic Resonance in Medicine (ISMRM 2021) (15-20 May), p. 1959.
  6. S. Chen, C. Eldeniz, W. Gan, U. S. Kamilov, T. Fraum, and H. An, “Forward-Fourier Motion-Corrected Reconstruction for Free-Breathing Liver DCE-MRI,” Proc. Int. Soc. of Magnetic Resonance in Medicine (ISMRM 2021) (15-20 May), p. 128.
  7. S. Chen, C. Eldeniz, W. Gan, U. S. Kamilov, D. Yang, M. Gach, and H. An, “Respiratory Motion Detection and Reconstruction Using CAPTURE and Deep Learning for a 0.35T MRI-LINAC System: An Initial Study,” Proc. Int. Soc. of Magnetic Resonance in Medicine (ISMRM 2021) (15-20 May), p. 4254.
  8. Y. Sun, J. Liu, Y. Sun, B. Wohlberg, and U. S. Kamilov, “Async-RED: A Provably Convergent Asynchronous Block Parallel Stochastic Method using Deep Denoising Priors,” Proc. Int. Conf. Learn. Represent. (ICLR 2021) (Vienna, Austria, May 4-8).
    [OpenReview] [arXiv:2010.01446] [Spotlight: 114/2997 = 4%]
  9. W. Gan, Y. Sun, C. Eldeniz, H. An and U. S. Kamilov, “Deep Image Reconstruction using Unregistered Measurements without Groundtruth,” Proc. Int. Symp. Biomedical Imaging 2021 (ISBI 2021) (Nice, France, April 13-16), pp. 1531-1534.
    [doi:10.1109/isbi48211.2021.9434079] [arXiv:2009.13986]
  10. W. Tahir, S. Gilbert, H. Wang, J. Zhu, U. S. Kamilov, and L. Tian, “Single-shot 3D holographic particle localization using deep priors trained on simulated data,” Proc. IS&T Electronic Imaging 2020 (Burlingame, CA, USA, January 26-30).

2020

  1. X. Xu, J. Liu, Y. Sun, B. Wohlberg, and U. S. Kamilov, “Boosting the Performance of Plug-and-Play Priors via Denoiser Scaling,” Proc. 54th Asilomar Conf. Signals, Systems, & Computers 2020, (Pacific Grove, CA, November 1–5), pp. 1305-1312.
    [doi:10.1109/ieeeconf51394.2020.9443410] [arXiv:2002.11546]
  2. W. Gan, C. Eldeniz, J. Liu, H. An, and U. S. Kamilov, “Image reconstruction for MRI using deep CNN priors trained without ground truth,” Proc. 54th Asilomar Conf. Signals, Systems, & Computers 2020, (Pacific Grove, CA, November 1–5), pp. 475-479.
    [doi:10.1109/ieeeconf51394.2020.9443403]
  3. X. Xu, O. Dhifallah, H. Mansour, P. T. Boufounos, and P. V. Orlik “Robust 3D Tomographic Imaging of the Ionospheric Electron Density,” Proc. Int. Geosci. Remote Sensing Symp. (IGARSS 2020) (Waikola, HI, USA, Sep 26-Oct 2), pp. 437-440.
    [doi:10.1109/igarss39084.2020.9324189] [merl:tr2020-113]
  4. C. Eldeniz, W. Gan, S. Chen, J. Liu, U. S. Kamilov, and H. An, “Phase2Phase: Reconstruction of free-breathing MRI into multiple respiratory phases using deep learning without a ground truth,” Proc. Int. Soc. of Magnetic Resonance in Medicine (ISMRM 2020) (8-14 August), p. 807.
    [ismrm2020-807]
  5. J. Liu, C. Eldeniz, Y. Sun, W. Gan, S. Chen, H. An, and U. S. Kamilov, “RED-N2N: Image reconstruction for MRI using deep CNN priors trained without ground truth,” Proc. Int. Soc. of Magnetic Resonance in Medicine (ISMRM 2020) (8-14 August), p. 993.
    [ismrm2020-993]
  6. T. Ge, U. Villa, U. S. Kamilov, and J. O’Sullivan, “Proximal Newton Methods for x-ray imaging with non-smooth regularization,” Proc. IS&T Electronic Imaging 2020 (Burlingame, CA, USA, January 26-30), pp. 007.
    [doi:10.2352/issn.2470-1173.2020.14.coimg-007] [arXiv:1912.01738]

2019

  1. J. Liu, Y. Sun, and U. S. Kamilov, “Infusing Learned Priors into Model-Based Multispectral Imaging,” Proc. 8th Int. Workshop on Computational Advances in Multi-Sensor Adaptive Process. (CAMSAP 2019) (Guadeloupe, France, December 15-18).
    [arXiv:1909.09313]
  2. Y. Sun, J. Liu, and U. S. Kamilov, “Block Coordinate Regularization by Denoising,” Proc. Ann. Conf. Neural Information Processing Systems (NeurIPS 2019) (Vancouver, Canada, December 8-14), pp. 382-392.
    [NeurIPS:8330] [arXiv:1905.05113] [Acceptance rate: 1428/6743 = 21%]
  3. Z. Wu, Y. Sun, J. Liu, and U. S. Kamilov, “Online Regularization by Denoising with Applications to Phase Retrieval,” Proc. IEEE Int. Conf. Comp. Vis. Workshops (ICCVW 2019) (Seoul, South Korea, Oct 27 – Nov 2), pp. 3887-3895.
    [doi:10.1109/iccvw.2019.00482] [cvf] [arXiv:1909.02040]
  4. J. Xing, U. S. Kamilov, W. Wu, Y. Wang, and M. Zhang, “Plug-and-Play Priors for Reconstruction-based Placental Image Registration,” Proc. Medical Image Computing and Computer-Assisted Intervention Workshops (MICCAIW) (Shenzhen, China, Oct 13-17), pp. 133–142.
    [doi:10.1007/978-3-030-32875-7_15] [arXiv:1909.01170]
  5. Y. Sun, S. Xu, Y. Li, L. Tian, B. Wohlberg, and U. S. Kamilov, “Regularized Fourier Ptychography using an Online Plug-and-Play Algorithm,” Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP 2019) (Brighton, UK, May 12-17), pp. 7665–7669.
    [doi:10.1109/icassp.2019.8683057]
  6. J. Liu, Y. Sun, X. Xu, and U. S. Kamilov, “Image Restoration using Total Variation Regularized Deep Image Prior,” Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP 2019) (Brighton, UK, May 12-17), pp. 7715–7719.
    [doi:10.1109/icassp.2019.8682856]
  7. X. Xu and U. S. Kamilov, “signProx: One-Bit Proximal Algorithm for Nonconvex Stochastic Optimization,” Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP 2019) (Brighton, UK, May 12-17), pp. 7800–7804.
    [doi:10.1109/icassp.2019.8682059]
  8. Y. Sun, B. Wohlberg, and U. S. Kamilov, “Plug-In Stochastic Gradient Method,” Proc. International Biomedical and Astronomical Signal Processing Frontiers Workshop (BASP 2019) (Villars-sur-Ollon, Switzerland, February 3-8), p. 75.
    [link]

2018

  1. Y. Sun and U. S. Kamilov, “Stability of Scattering Decoder For Nonlinear Diffractive Imaging,” Proc. 4th International Traveling Workshop on Interactions between Sparse models and Technology (iTWIST 2018) (Marseille, France, November 21-23), p. 31.
    [arXiv:1806.08015]
  2. D. Liu, H. Mansour, P. T. Boufounos, and U. S. Kamilov “Robust sensor localization based on Euclidean distance matrix,” Proc. Int. Geosci. Remote Sensing Symp. (IGARSS 2018) (Valencia, Spain, July 23-27), pp. 7998-8001.
    [doi:10.1109/IGARSS.2018.8517324]
  3. Y. Ma, H. Mansour, D. Liu, P. T. Boufounos, and U. S. Kamilov “Nonconvex optimization for diffractive imaging,” Proc. OSA Mathematics in Imaging (MATH 2018) (Orlando, FL, USA, June 25-28), MW5D.3.
    [doi:10.1364/MATH.2018.MW5D.3]
  4. W. Tahir, U. S. Kamilov, and L. Tian “Sampling and processing for multiple scattering in inline compressive holography,” Proc. OSA Applications of Lasers for Sensing and Free Space Communications 2018 (LS&C 2018) (Orlando, FL, USA, June 25-28), JTh3B.1.
    [doi:10.1364/3D.2018.JTh3B.1]
  5. H. Mansour, U. S. Kamilov, D. Liu, and P. T. Boufounos, “Radar Autofocus using Sparse Blind Deconvolution,” Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP 2018) (Calgary, Canada, March 15-20), pp. 1623-1627.
    [doi:10.1109/icassp.2018.8462402] [merl:tr2018-003]
  6. B. Wen, U. S. Kamilov, D. Liu, H. Mansour, and P. T. Boufounos, “DeepCASD: An End-to-End Approach for Multi-spectral Image Super-Resolution,” Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP 2018) (Calgary, Canada, March 15-20), pp. 6503-6507.
    [doi:10.1109/icassp.2018.8461795] [merl:tr2018-009]
  7. Y. Ma, H. Mansour, D. Liu, P. T. Boufounos, U. S. Kamilov, “Accelerated Image Reconstruction for Nonlinear Diffractive Imaging,” Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP 2018) (Calgary, Canada, March 15-20), pp. 6473-6477.
    [doi:10.1109/icassp.2018.8462400] [merl:tr2018-008]

2017

  1. K. Kojima, B. Wang, U. S. Kamilov, T. Koike-akino, and K. Parsons, “Acceleration of FDTD-based Inverse Design Using a Neural Network Approach,” Proc. OSA Advanced Photonics Congress 2017 (New Orleans, LA, USA, September 24-27), ITu1A.4.
    [doi:10.1364/IPRSN.2017.ITu1A.4]
  2. K. Degraux, U. S. Kamilov, P. T. Boufounos, and D. Liu, “Online Convolutional Dictionary Learning for Multimodal Imaging,” Proc. IEEE Int. Conf. Image Proc. (ICIP 2017) (Beijing, China, September 17-20), pp. 1617-1621.
    [doi:10.1109/ICIP.2017.8296555] [arXiv:1706.04256]
  3. Y. Ma, D. Liu, H. Mansour, U. S. Kamilov, Y. Taguchi, P. T. Boufounos, and A. Vetro, “Fusion of multi-angular aerial Images based on epipolar geometry and matrix completion,” Proc. IEEE Int. Conf. Image Proc. (ICIP 2017) (Beijing, China, September 17-20), pp. 1197-1201.
    [doi:10.1109/ICIP.2017.8296471]
  4. M. H. Shoreh, A. Goy, J. Lim, U. S. Kamilov, M. Unser, and D. Psaltis, “Imaging cell clusters and tissue using learning tomography,” Proc. SPIE Optical Methods for Inspection, Characterization, and Imaging of Biomaterials III, 1033306, 26 June 2017.
    [doi:10.1117/12.2275250]
  5. H.-Y. Liu, D. Liu, H. Mansour, P. T. Boufounos, L. Waller, and U. S. Kamilov, “SEAGLE: Robust Computational Imaging under Multiple Scattering,” Proc. OSA Mathematics in Imaging (MATH 2017) (St. Francisco, CA, USA, June 26-29), MM4C.1.
    [doi:10.1364/MATH.2017.MM4C.1]
  6. U. S. Kamilov, H. Mansour, and D. Liu, “Learning Convolutional Proximal Filters,” Proc. 7th Workshop on Signal Process. with Adaptive Sparse Structured Representations (SPARS 2017) (Lisbon, Portugal, June 5-8), p. 101.
    [merl:tr2017-074]
  7. H. Mansour, U. S. Kamilov, and O. Yilmaz, “A Kaczmarz Method for Low Rank Matrix Recovery,” Proc. 7th Workshop on Signal Process. with Adaptive Sparse Structured Representations (SPARS 2017) (Lisbon, Portugal, June 5-8), p. 60.
    [merl:tr2017-073]
  8. H.-Y. Liu, U. S. Kamilov, D. Liu, H. Mansour, and P. T. Boufounos, “Compressive Imaging with Iterative Forward Models,” Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP 2017) (New Orleans, USA, March 5-9), pp. 6025-6029.
    [doi:10.1109/ICASSP.2017.7953313] [ICASSP 2017 Student Paper Award finalist]
  9. M. H. Shoreh, A. Goy, J. Lim, U. S. Kamilov, M. Unser, and D. Psaltis, “Optical Tomography based on a Nonlinear Model that Handles Multiple Scattering,” Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP 2017) (New Orleans, USA, March 5-9), pp. 6220-6224.
    [doi:10.1109/ICASSP.2017.7953352]
  10. U. S. Kamilov and H. Mansour, “Learning Bayesian Optimal FISTA with Error Backpropagation,” Proc. International Biomedical and Astronomical Signal Processing Frontiers Workshop (BASP 2017) (Villars-sur-Ollon, Switzerland, January 29-February 3), p. 66.
    [basp-proc-2017]

2016

  1. D. Liu, U. S. Kamilov, and P. T. Boufounos, “Compressive Tomographic Radar Imaging with Total Variation Regularization,” Proc. IEEE 4th International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar, and Remote Sensing (CoSeRa 2016) (Aachen, Germany, September 19-22), pp. 120-123.
    [doi:10.1109/cosera.2016.7745712]
  2. D. Liu, U. S. Kamilov, and P. T. Boufounos, “Coherent Distributed Array Imaging under Unknown Position Perturbations,” Proc. IEEE 4th International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar, and Remote Sensing (CoSeRa 2016) (Aachen, Germany, September 19-22), pp. 105-109.
    [doi:10.1109/cosera.2016.7745709]
  3. H. Mansour, U. S. Kamilov, D. Liu, P. Orlik, P. T. Boufounos, K. Parsons, and A. Vetro, “Online Blind Deconvolution for Sequential Through-the-Wall-Radar-Imaging,” Proc. IEEE 4th International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar, and Remote Sensing (CoSeRa 2016) (Aachen, Germany, September 19-22), pp. 61-65.
    [doi:10.1109/cosera.2016.7745700]
  4. U. S. Kamilov and H. Mansour, “Learning MMSE Optimal Thresholds for FISTA,” Proc. 3rd International Traveling Workshop on Interactions between Sparse models and Technology (iTWIST 2016) (Aalborg, Denmark, August 24-26), p. 42.
    [merl:tr2016-111]
  5. U. S. Kamilov, “Minimizing Isotropic Total Variation without Subiterations,” Proc. 3rd International Traveling Workshop on Interactions between Sparse models and Technology (iTWIST 2016) (Aalborg, Denmark, August 24-26), p. 39.
    [merl:tr2016-109]
  6. U. S. Kamilov, I. Papadopoulos, M. Hashemi, A. Goy, M. Unser, and D. Psaltis, “Learning From Examples in Optical Imaging,” Proc. OSA Computational Optical Sensing and Imaging Conference (COSI 2016) (Heidelberg, Germany, July 25-28), CT1D.1.
    [doi:10.1364/cosi.2016.ct1d.1]
  7. U. S. Kamilov and P. T. Boufounos, “Depth Superresolution using Motion Adaptive Regularization,” Proc. IEEE Int. Conf. Multimedia & Expo Workshops (ICMEW 2016) (Seattle, WA, USA, July 11-15), pp. 1-6.
    [doi:10.1109/icmew.2016.7574677]
  8. U. S. Kamilov, “Parallel proximal methods for total variation minimization,” Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP 2016) (Shanghai, China, March 20-25), pp. 4697—4701.
    [doi:10.1109/icassp.2016.7472568]
  9. J. Castorena, U. S. Kamilov, and P. T. Boufounos, “Autocalibration of Lidar and Optical Cameras via Edge Alignment,” Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP 2016) (Shanghai, China, March 20-25), pp. 2862—2866.
    [doi:10.1109/icassp.2016.7472200]
  10. H. Mansour and U. S. Kamilov, “Multipath Removal by Online Blind Deconvolution in Through-the-Wall-Imaging,” Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP 2016) (Shanghai, China, March 20-25), pp. 3106—3110.
    [doi:10.1109/icassp.2016.7472249]

2015

  1. H. Handa, H. Mansour, D. Liu, and U. S. Kamilov, “Extended Target Localization with Total-Variation Denoising in Through-the-Wall-Imaging,” Proc. Int. Workshop on Computational Advances in Multi-Sensor Adaptive Process. (CAMSAP 2015) (Cancun, Mexico, December 13-16), pp. 445–448.
    [doi:10.1109/camsap.2015.7383832]
  2. D. Liu, U. S. Kamilov, and P. T. Boufounos, “Sparsity-Driven Distributed Array Imaging,” Proc. Int. Workshop on Computational Advances in Multi-Sensor Adaptive Process. (CAMSAP 2015) (Cancun, Mexico, December 13-16), pp. 441–444.
    [doi:10.1109/camsap.2015.7383831]
  3. S. Rangan, A. K. Fletcher, P. Schniter, and U. S. Kamilov, “Inference for Generalized Linear Models via Alternating Directions and Bethe Free Energy Minimization,” Proc. IEEE Int. Symp. Inform. Theory (ISIT 2015) (Hong Kong, June 14-19), pp. 1640–1644.
    [doi:10.1109/isit.2015.7282734]

2013

  1. U. S. Kamilov, A. Bourquard, and M. Unser, “Sparse Image Deconvolution with Message Passing,” Proc. Workshop on Signal Process. with Adaptive Sparse Structured Representations (SPARS 2013) (Lausanne, Switzerland, July 8-11).
    [big:kamilov1302]
  2. E. Bostan, U. S. Kamilov, M. Nilchian, and M. Unser, “Consistent Discretization of Linear Inverse Problems using Sparse Stochastic Processes,” Proc. Workshop on Signal Process. with Adaptive Sparse Structured Representations (SPARS 2013) (Lausanne, Switzerland, July 8-11).
    [big:bostan1304]
  3. E. Bostan, J. Fageot, U. S. Kamilov, and M. Unser, “MAP Estimators for Self-Similar Sparse Stochastic Models,” Proc. International Conference on Sampling Theory and Applications (SAMPTA 2013) (Bremen, Germany, July 1-5), pp. 197—199.
    [sampta2013:p197]
  4. U. S. Kamilov, A. Bourquard, E. Bostan, and M. Unser, “Autocalibrated Signal Reconstruction from Linear Measurements using Adaptive GAMP,” Proc. IEEE. Int. Conf. Acoustics, Speech and Signal Process. (ICASSP 2013) (Vancouver, Canada, May 26-31), pp. 5925-5928.
    [doi:10.1109/icassp.2013.6638801]
  5. B. Tekin, U. S. Kamilov, E. Bostan, and M. Unser, “Benefits of Consistency in Image Denoising with Steerable Wavelets,” Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP 2013) (Vancouver, Canada, May 26-31), pp. 1355-1358.
    [doi:10.1109/icassp.2013.6637872]

2012

  1. U. S. Kamilov, S. Rangan, A. K. Fletcher, and M. Unser, “Approximate Message Passing with Consistent Parameter Estimation and Applications to Sparse Learning,” Proc. Ann. Conf. Neural Information Processing Systems (NIPS 2012) (Lake Tahoe, Nevada, December 3-6), pp. 2447-2455.
    [nips:4498] [Acceptance rate: 370/1467 = 25%]
  2. A. Amini, U. S. Kamilov, and M. Unser, “The Analog Formulation of Sparsity Implies Infinite Divisibility and Rules Out Bernoulli-Gaussian Priors,” Proc. IEEE Information Theory Workshop 2012 (ITW 2012) (Lausanne, Switzerland, September 3-7), pp. 687-691.
    [doi:10.1109/itw.2012.6404765]
  3. E. Bostan, U. S. Kamilov, and M. Unser, “Reconstruction of Biomedical Images and Sparse Stochastic Modeling,” Proc. Int. Symp. Biomedical Imaging 2012 (ISBI 2012) (Barcelona, Spain, May 2-5), pp. 880-883.
    [doi:10.1109/isbi.2012.6235689]
  4. U. S. Kamilov, A. Amini, and M. Unser, “MMSE Denoising of Sparse Lévy Processes via Message Passing,” Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP 2012) (Kyoto, Japan, March 25-30), pp. 3637-3640.
    [doi:10.1109/ICASSP.2012.6288704]
  5. U. S. Kamilov, E. Bostan, and M. Unser, “Generalized Total Variation Denoising via Augmented Lagrangian Cycle Spinning with Haar Wavelets,” Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP 2012) (Kyoto, Japan, March 25-30), pp. 909-912.
    [doi:10.1109/icassp.2012.6288032]
  6. A. Amini, U. S. Kamilov, and M. Unser, “Bayesian Denoising of Generalized Poisson Processes with Finite Rate of Innovation,” Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP 2012) (Kyoto, Japan, March 25-30), pp. 3629-3632.
    [doi:10.1109/icassp.2012.6288702]

2011

  1. U. S. Kamilov, V. K. Goyal, and S. Rangan, “Generalized Approximate Message Passing Estimation from Quantized Samples,” Proc. 4th Int. Workshop on Computational Advances in Multi-Sensor Adaptive Process. (CAMSAP 2011) (San Juan, Puerto Rico, December 13-16), pp. 401-404.
    [10.1109/camsap.2011.6136027] [CAMSAP 2011 Student Paper Award finalist]
  2. U. S. Kamilov, V. K. Goyal, and S. Rangan, “Message-Passing Estimation from Quantized Samples,” Proc. 4th Workshop on Signal Process. with Adaptive Sparse Structured Representations (SPARS 2011) (Edinburgh, United Kingdom, June 27-June 30), p. 58.
    [link]
  3. U. S. Kamilov, V. K. Goyal, and S. Rangan, “Optimal Quantization for Compressive Sensing under Message Passing Reconstruction,” Proc. 2011 IEEE Int. Symp. Inform. Theory (ISIT 2011) (Saint-Petersburg, Russia, July 31-August 5), pp. 390-394.
    [doi:isit.2011.6034168]