Recent Publications

 

(Updated June 2021 …)

  • S. Zeng, A. Anwar, T. Doan, A. Raychowdhury, J. Romberg, “A decentralized policy gradient approach to multi-task reinforcement learning,” Uncertainty in Artificial Intelligence (UAI), (Virtual Only), July 2021. [UAI]
  • T. Doan, S. T. Maguluri, and J. Romberg, “Fast convergence rates of distributed subgradient methods with adaptive quantization,” IEEE Trans. Automatic Control, vol. 66, no. 5, pp. 2191–2205, May 2021. [IEEE}
  • E. Huang, C. DeLude, J. Romberg, S. Mukhopadhyay, M. Swaminathan, “Anisotropic scatterer models for representing RCS of complex objects,” IEEE Radar Conference, Atlanta, GA, May 2021. [IEEE]
  • S. Kampezidou, J. Romberg, K. G. Vamvoudakis, D. Mavris, “Online adaptive learning in energy trading Stackelberg games with time-coupling constraints,” American Control Conference (ACC), New Orleans, LA, May 2021.
  • J. Gao, R. S. Srinivasa, C. Qian, L. M. Glass, J. Spaeder, J. Romberg, J. Sun, and C. Xiao, “STAN: Spatio-temporal attention network for pandemic prediction using real-world evidence,” J. American Medical Informatics Association (JAMIA), vol. 28, no. 4, pp. 733–743, March 2021. [JAMIA]
  • S. Karnik, J. Romberg, M. A. Davenport, “Improved bounds for the eigenvalues of prolate spheroidal wave functions and discrete prolate spheroidal sequences,” Applied and Computational Harmonic Analysis, vol. 55, pp. 97–128, 2021. [ACHA]
  • K. Lee, S. Bahmani, Y. Eldar, and J. Romberg, “Phase retrieval of low-rank matrices by anchored regression,” Information and Inference, vol. 10, no. 1, pp. 285–332, March 2021. [OUP]
  • P. L. Brown, M. O’Shaughnessy, C. Rozell, J. Romberg, M. Flynn, “A 17.8 MS/s Compressed Sensing Radar Accelerator Using a Spiking Neural Network,” IEEE J. Solid-State Circuits, vol. 56, no. 3, pp. 834–843, March 2021. [IEEE]
  • C. DeLude, D. Munzer, H. Wang, J. Romberg, “Low-dimensional encoding based broadband beam- forming algorithm for 5G communications,” GOMACTECH, Charleston, SC, March 2021.
  • F. Karimzadeh, N. Cao, B. Crafton, J. Romberg, A. Raychowdhury, “A hardware-friendly approach towards sparse neural networks based on LFSR-generated pseudo-random sequences,” IEEE Trans. Circuits and Systems, vol. 68, no. 2, pp. 751–764, February 2021. [IEEE]
  • T. Doan, S. T. Maguluri, and J. Romberg, “Finite-Time Performance of Distributed Temporal Difference Learning with Linear Function Approximation,” SIAM J. Mathematics of Data Science, vol. 3, no. 1, pp. 298–320, 2021. [SIAM]
  • A. Mcrae, J. Romberg, and M. A. Davenport,“Sample complexity and effective dimension for regression on manifolds,” Neural Information Processing Systems (NeurIPS), (Virtual Only), December 2020. [NeurIPS]
  • T. Miyano, J. Romberg, and M. Egerstedt, “Distributed Force/Position Optimization Dynamics for Cooperative Unknown Payload Manipulation,” Conference on Decision and Control (CDC), Jeju Island, Korea, December 2020. [IEEE]
  • S. Xu, F. Wang, H. Wang, J. Romberg, “In-Field Performance Optimization for Mm-Wave Mixed- Signal Doherty Power Amplifiers: A Bandit Approach,” IEEE Trans. Circuits and Systems, vol. 67, no. 12, pp. 5302–5315, December 2020. [IEEE]
  • S. Bahmani and J. Romberg, “Convex programming for estimation in nonlinear recurrent models,” J. Machine Learning Research, vol. 21, no. 235, pp. 1–20, 2020. [JMLR]
  • R. S. Srinivasa, K. Lee, and J. Romberg,“Tensor-norm-based convex program and performance guarantee for subspace-constrained blind deconvolution,” IEEE Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, California, November 2020.
  • N. Tian, K. Lee, J. Romberg, N. Durofchalk, K. G. Sabra, “Blind deconvolution of sources of opportunity in ocean waveguides using bilinear channel models,” J. Acoustical Soc. America, vol. 148, no. 4, pp. 2267-2279, October 2020. [JASA]
  • T. Doan, S. T. Maguluri, and J. Romberg,“Convergence Rates of Distributed Gradient Methods Under Random Quantization: A Stochastic Approximation Approach,” accepted to IEEE Trans. Automatic Control, October 2020; early access [IEEE].
  • T. Miyano, J. Romberg, and M. Egerstedt, “Primal-dual gradient dynamics for cooperative unknown payload manipulation without communication,” American Control Conference (ACC), Denver, CO, July 2020. [IEEE]
  • T. Doan and J. Romberg, “Finite-time performance of distributed two-time-scale stochastic approximation,” Learning for Dynamics and Control (L4DC), Berkeley, CA, June 2020. [PMLR]
  • R. S. Srinivasa, M. A. Davenport, and J. Romberg, “Sample complexity bounds for localized sketching,” Int. Conf. Artificial Intelligence and Statistics (AISTATS), Palermo, Italy, June 2020. [PMLR]
  • F. Karimzadeh, N. Cao, B. Crafton, J. Romberg, and A. Raychowdhury, “Hardware-aware pruning of DNNs using LFSR-generated pseudo-random indices,” IEEE Int. Symp. Circuits and Systems (ISCAS), Seville, Spain, May 2020. [IEEE]
  • S. Xu, F. Wang, J. Romberg, and H. Wang, “Optimal control for mm-Wave mixed-signal Doherty power amplifier: A bandit-problem approach,” to appear at Gov. Microcircuit Applications and Critical Technologies (GOMACTech), San Diego, California, March 2020. [IEEE]
  • M. Chang, L-H. Lin, J. Romberg, A. Raychowdhury, “OPTIMO: A 65nm 279GOPS/W 16b programmable spatial-array processor with on-chip network for solving distributed optimizations via the alternating direction method of multipliers,” IEEE J. Solid State Circuits, vol. 55, no. 3, pp. 629–638, March 2020. [IEEE]
  • A. Aghasi, A. Abdi, and J. Romberg, “Fast convex pruning of deep neural networks,” SIAM J. Mathematics of Data Science, vol. 2, no. 1, pp. 158–188, February 2020. [SIAM]
  • 
R. S. Srinivasa, M. Davenport, J. Romberg, “Trading beams for bandwidth: Imaging with randomized beamforming,” SIAM J. Imaging Science, vol. 13, no. 1, pp. 317–350, February 2020. [SIAM]
  • A. Ahmed and J. Romberg, “Compressive sampling of ensembles of correlated signals,” IEEE Transactions on Information Theory, vol. 66, no. 2, pp. 1078–1098, February 2020. 
[IEEE]
  • R. S. Srinivasa, K. Lee, M. Junge, and J. Romberg, “Decentralized sketching of low-rank matrices,” Neural Information Processing Systems (NeurIPS), Vancouver, BC, Canada, December 2019. [NeurIPS]
  • T. Hamam and J. Romberg, “Second-order filtering algorithm for streaming optimization problems,” IEEE Computational Advances in Multi-Sensor Adaptive Processing, Guadeloupe, West Indies, December 2019. [IEEE]
  • I. Yoon, M. Chang, K. Ni, M. Jerry, S. Gangopadhyay, G. Smith, T. Hamam, V. Narayanan, J. Romberg, S-L. Lu , S. Datta, and A. Raychowdhury, “A FerroFET based in-memory processor for solving distributed and iterative optimizations via least-squares method,” IEEE J. Exploratory Solid- State Computational Devices, vol. 5, no. 2, pp. 132–141, December 2019. [IEEE]
  • T. Doan and J. Romberg, “Linear two-time-scale stochastic approximation: A finite-time analysis,” 57th Annual Allerton Conference, Urbana-Champaign, Illinois, September 2019. [allerton]
  • T. Doan, S. T. Maguluri, and J. Romberg, “Convergence rates of distributed two-time-scale gradient methods under random quantization,” 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems (NecSys), Chicago, IL, September 2019. [ScienceDirect]
  • S. Bahmani and J. Romberg, “Anchored regression: Solving nonlinear equations via convex programming,” Foundations of Computational Mathematics, vol. 19, no. 4, pp. 813–841, 2019. 
[Springer]
  • K. L. Fair, D. Mendat, A. Andreou, C, Rozell, J. Romberg, D. V. Anderson, “Sparse coding Using the locally competitive algorithm on the TrueNorth neurosynaptic system,” Frontiers in Neuroscience, vol. 13, article 754, July 2019. [Frontiers]
  • K. Beale, J. Chen, K. Kelly, and J. Romberg, “A hardware realization of superresolution combining random coding and blurring,” IEEE Transactions on Computational Imaging, vol. 5, no. 4, pp. 366-380, September 2019. [IEEE]
  • S. Bahmani and J. Romberg, “Solving Equations of Random Convex Functions via Anchored Regression,” Foundations of Computational Mathematics, vol. 19, no. 4, pp. 813-841, August 2019. [arxiv][Springer]
  • K. Lee, R. S. Srinivasa, M. Junge, and J. Romberg, “Entropy estimates on tensor products of Banach spaces and applications to low-rank recovery,” Sampling Theory and Applications (SampTA), Bordeaux, France, July 2019. [SAMPTA]
  • S. Karnik, J. Romberg, and M. Davenport, “Fast multitaper spectral estimation,” Sampling Theory and Applications (SampTA), Bordeaux, France, July 2019. [SAMPTA]
  • S. Karnik, J. Romberg, and M. Davenport, “Bandlimited signal reconstruction from nonuniform samples,” SPARS Workshop, Toulouse, France, July 2019.
  • T. Doan, S. T. Maguluri, and J. Romberg,“Convergence rates of distributed TD(0) with linear function approximation for multi-agent reinforcement learning,” Int. Conf. Machine Learning (ICML), Long Beach, California, June 2019. [arxiv][PMLR]
  • S. Karnik, Z. Zhu, M. B. Wakin, J. Romberg, and M. A. Davenport, “The fast Slepian transform,” Applied and Computational Harmonic Analysis, vol. 46, no. 3, pp. 624–652, May 2019. [arxiv] [ACHA]
  • S. Xu, S. Zeng, and J. Romberg, “Fast compressive sensing recovery using generative models with structured latent variables,” IEEE Conference on Acoustics, Speech, and Signal Processing (ICASSP), Brighton, UK, May 2019. [IEEE]
  • T. Doan, S. T. Maguluri, and J. Romberg, “On the convergence of distributed subgradient methods under quantization,” 56th Annual Allerton Conference, Urbana-Champaign, Illinois, October 2018. [IEEE]
  • R. Srinivasa, M. Davenport, and J. Romberg, “Localized random projections with applications to coherent array imaging,” 56th Annual Allerton Conference, Urbana-Champaign, Illinois, October 2018. [IEEE]
  • Z. Zhu, S. Karnik, M. B. Wakin, M. A. Davenport, J. Romberg, “ROAST: Rapid orthogonal approximate Slepian transform,” IEEE Transactions on Signal Processing, vol. 66, no. 22, pp. 5887– 5901, 2018. [arxiv][IEEE]
  • K. Lee, F. Krahmer, and J. Romberg, “Spectral methods for passive imaging: Non-asymptotic performance and robustness,” SIAM Journal on Imaging Sciences, vol. 11, no. 3, pp. 2110-2164, 2018. [arxiv][SIAM]
  • S. Bahmani, P. Tetali, and J. Romberg, “Algebraic connectivity under site percolation in finite weighted graphs,” IEEE Transactions on Network Science and Engineering, vol. 5, no. 2, pp. 86–91, 2018. [arxiv][IEEE]
  • K. Lee, N. Tian, and J. Romberg, “Fast and guaranteed blind multichannel deconvolution under a bilinear system model,” IEEE Transaction on Information Theory, vol. 64, no. 7, pp. 4792–4818, 2018.  [arxiv] [IEEE]
  • A. Aghasi, A. Abdi, and J. Romberg, “Fast convex pruning of deep neural networks,” June 2018. [arxiv]
  • A. Aghasi and J. Romberg, “Extracting the principal shape components via convex programming,” IEEE Transactions on Image Processing, vol. 27, no. 7, April 2018.  [IEEE]
  • Z. Zhu, S. Karnik, M. A. Davenport, J. Romberg, M. B. Wakin, “The eigenvalue distribution of discrete time-frequency limiting operators,” IEEE Signal Processing Letters, vol. 25, no. 1, January 2018. [IEEE], [arxiv]
  • A. Aghasi, A. Abdi, N. Nguyen, and J. Romberg, “Net-Trim: A layer-wise convex pruning of deep neural networks,” NIPS, December 2017. [NIPS], [pdf], [youtube]
  • A. Amaravati, S. Xu, J. Romberg, A. Raychowdhury, “A 65nm compressive-sensing time-based ADC with embedded classification and INL-aware training for arrhythmia detection,” BioCAS, October 2017. [pdf]
  • S. Bahmani and J. Romberg, “A flexible convex relaxation for phase retrieval,” Electronic Journal of Statistics, vol. 11, no. 2 (2017), 5254-5281. [EJS] [pdf]
  • K. Lee, N. Tian, J. Romberg, “Performance guarantees of spectral methods for passive sensing of multiple channels,” DSP Conf., August 2017. [IEEE] [pdf]
  • A. Anvesha, S. Xu, N. Cao, J. Romberg, and A. Raychowdhury, “A light-powered smart camera with compressed domain gesture detection,” IEEE Trans. Circuits and Systems for Video Technology, July 2017. [IEEE]
  • K. Lee, F. Krahmer, and J. Romberg, “An eigen approach to stable multichannel blind deconvolution under an FIR subspace model,” SAMPTA, July 2017. [pdf]  [IEEE]
  • N. Tian, S-H. Byun, K. Sabra, and J. Romberg, “Multichannel myopic deconvolution in underwater acoustic channels via low-rank recovery,” J. Acoustical Soc. America, 141, 3337, May 2017. [JASA][pdf]
  • S. Bahmani and J. Romberg, “Phase retrieval meets statistical learning theory: A flexible convex relaxation,” AISTATS, April 2017. [pdf]
  • N. Zachariah, J. Langley, J. Romberg, X. P. Hu, “Faster than mulitband … Advanced Pseudo Fourier Imaging’s (API) response to the current state of the art,” ISMRM, April 2017.  [ISMRM]
  • A. Amaravati, S. Xu, J. Romberg, and A. Raychowdhury, “A 130nm 165nJ/frame compressed-domain camera front end with mixed-signal smashed filter Classifier for ‘in-sensor’ analytics in smart cameras,” IEEE Trans. Circuits and Systems II: Express Briefs, April 2017.  [IEEE]
  • J. Romberg, “Sampling and reconstruction in the 21st century,” ICASSP, March 2017. [IEEE][pdf]
  • S. Xu, A. Amaravati, J. Romberg, and A. Raychowdhury, “Appearance-based gesture recognition in the compressed domain,” ICASSP, March 2017.  [IEEE]
  • Z. Zhu, S. Karnik, M. B. Wakin, M. A. Davenport, and J. Romberg, “Fast orthogonal approximations of sampled sinusoids and bandlimited signals,” ICASSP, March 2017.  [IEEE]
  • S. Karnik, Z. Zhu, M. B. Wakin, J. Romberg, and M. A. Davenport, “Fast Computations for Approximation and Compression in Slepian Spaces,” GlobalSIP, December 2016.  [IEEE]
  • L. F. Jorver, J. Romberg, and J. Weitz, “Inferring phage–bacteria infection networks from time-series data,” Royal Society Open Science, November 2016. [rs] [biorxiv]
  • A. Redo-Sanchez, B. Heshmat, A. Aghasi, S, Naqvi, M. Zhang, J. Romberg, and R. Raskar, “Terahertz time-gated spectral imaging for content extraction through layered Structures,” Nature Communications, vol. 7, September 9, 2016. [ncomm]
  • A. Aghasi and J. Romberg, Learning Shapes by Convex Composition, Preprint, July 2016.  [arxiv]
  • A. Aghasi, B. Heshmat, A. Redo-Sanchez, J. Romberg, R. Raskar, Blind Demodulation: Defringing of Interreflections in Time Domain THz Spectroscopy, Optica 3(7), 754-762, 2016.
  • A. Amaravati, S. Xu, N. Cao, J. Romberg, A. Raychowdhury, A Light-powered, “Always-On” Smart Camera with Compressed Domain Gesture Detection, ISLPED, August 2016.
  • M. Davenport and J. Romberg, An Overview of Low-Rank Matrix Recovery from Incomplete Observations, Journal on Special Topics in Signal Processing, vol. 10, no. 4, pp. 608–622, 2016.
  • S. Bahmani and J. Romberg, “Near-Optimal Estimation of Simultaneously Sparse and Low-Rank Matrices from Nested Linear Measurements,” to appear in Information and Inference, published on- line May 2016.
  • S. Bahmani and J. Romberg, ”Efficient Compressive Phase Retrieval with Constrained Sensing Vectors,” Neural Information Processing Systems, Montreal, Canada, December 2015.
  • S. Bahmani and J.Romberg, ”Sketching for Simultaneously Sparse and Low-Rank Covariance Matrices,” IEEE Computational Advances in Multi-Sensor Adaptive Processing, Cancun, Mexico, December 2015.
  • A. Aghasi and J.Romberg, “Convex cardinal shape composition,” SIAM Journal on Imaging Science, vol. 8, no. 4, pp. 2887–2950, 2015.
  • S. Bahmani and J. Romberg, “Compressive deconvolution in random mask imaging,” IEEE Transactions on Computational Imaging, vol. 1, no. 4, pp. 236–246, 2015.
  • S. Bahmani and J. Romberg, “Lifting for Blind Deconvolution in Random Mask Imaging: Identifiability and Convex Relaxation,” SIAM Journal on Imaging Science, vol. 8, no. 4, pp. 2203–2238, 2015.
  • W. Mantzel and J. Romberg, “Compressed Subspace Matching on the Continuum,” Information and Inference, vol. 4, no. 2, pp. 79–107, 2015.
  • A. Balavoine, J. Romberg, and C. Rozell, “Discrete and continuous iterative soft thresholding with a dynamic input,” IEEE Transactions on Signal Processing, vol. 63, no. 12, pp. 3165–3176, 2015.
  • A. Ahmed and J. Romberg, “Compressive Multiplexing of Correlated Signals,” IEEE Transactions on Information Theory, vol. 61, no. 1, pp. 479–498, 2015.
  • C. Turnes, D. Balcan, and J. Romberg, “Superfast Tikhonov Regularization of Toeplitz Systems,” IEEE Transactions on Signal Processing, vol. 62, no. 15, pp. 3809–3821, 2014.
  • K. Sabra, J. Romberg, S. Lani, and F. L. Degertekin, “High-frequency passive ultrasonics at sub- Nyquist rates using TM noise,” Journal of the Acoustical Society of America, vol. 135, no. 6, pp. EL364–370, 2014.
  • A. Ahmed, B. Recht, and J. Romberg, “Blind Deconvolution using Convex Programming,” IEEE Transactions on Information Theory, vol. 60, no. 3, pp. 1711–1732, 2014.
  • W. Mantzel, J. Romberg, and K. Sabra, “Round-Robin Multiple-Source Localization,” Journal of the Acoustical Society of America, vol. 134, no. 1, pp. 134–147, 2014.
  • M. S. Asif and J. Romberg, “Sparse recovery of streaming signals using l1 homotopy,” IEEE Transactions on Signal Processing, vol. 62, no. 16, pp. 4209–4223, 2014.
  • S. Yang, J. Huang, A. Lall, J. Romberg, and J. Xu, “Error estimating codes for insertion and deletion channels,” SIGMETRICS, Austin, Texas, June 2014.