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ORCIDJustin K. Romberg
Justin Romberg
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- affiliation: Georgia Institute of Technology, Atlanta, School of Electrical and Computer Engineering
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2020 – today
- 2025
[c92]Xiangyu Mao, Coleman DeLude, Wei-Chun Wang, Justin Romberg, Saibal Mukhopadhyay:
Fully Digital Ultra-low-bit Linear Embedding Beamforming System with Quantization Compensation. RWS 2025: 13-16- [i61]Yitao Bai, Sihan Zeng, Justin Romberg, Thinh T. Doan:
Accelerating Multi-Task Temporal Difference Learning under Low-Rank Representation. CoRR abs/2503.02030 (2025) - 2024
- [j59]Sihan Zeng
, Thinh T. Doan, Justin Romberg:
A Two-Time-Scale Stochastic Optimization Framework with Applications in Control and Reinforcement Learning. SIAM J. Optim. 34(1): 946-976 (2024) - [j58]Tatsuya Miyano, Justin Romberg, Magnus Egerstedt:
Globally Optimal Assignment Algorithm for Collective Object Transport Using Air-Ground Multirobot Teams. IEEE Trans. Control. Syst. Technol. 32(1): 258-265 (2024) - [j57]Styliani I. Kampezidou, Justin Romberg, Kyriakos G. Vamvoudakis, Dimitri N. Mavris:
Decentralized and Privacy-Preserving Learning of Approximate Stackelberg Solutions in Energy Trading Games With Demand Response Aggregators. IEEE Trans. Syst. Man Cybern. Syst. 54(10): 6304-6319 (2024) - [c91]Thomy Phan, Joseph Driscoll, Justin Romberg, Sven Koenig:
Confidence-Based Curriculum Learning for Multi-Agent Path Finding. AAMAS 2024: 1558-1566 - [c90]Alex Saad-Falcon, Brighton Ancelin, Justin Romberg:
Subspace Tracking with Dynamical Models on the Grassmannian. SAM 2024: 1-5 - [c89]Chiraag Kaushik, Justin Romberg, Vidya Muthukumar:
Precise asymptotics of reweighted least-squares algorithms for linear diagonal networks. NeurIPS 2024 - [c88]Nael Mizanur Rahman, Sudarshan Sharma, Coleman DeLude, Wei Chun Wang, Justin Romberg, Saibal Mukhopadhyay:
BeamCIM: A Compute-In-Memory based Broadband Beamforming Accelerator using Linear Embedding. RWS 2024: 46-49 - [i60]Thomy Phan, Joseph Driscoll, Justin Romberg, Sven Koenig:
Confidence-Based Curriculum Learning for Multi-Agent Path Finding. CoRR abs/2401.05860 (2024) - [i59]Sihan Zeng, Thinh T. Doan, Justin Romberg:
Natural Policy Gradient and Actor Critic Methods for Constrained Multi-Task Reinforcement Learning. CoRR abs/2405.02456 (2024) - [i58]Chiraag Kaushik, Justin Romberg, Vidya Muthukumar:
Precise asymptotics of reweighted least-squares algorithms for linear diagonal networks. CoRR abs/2406.02769 (2024) - [i57]Brighton Ancelin, Alex Saad-Falcon, Kason Ancelin, Justin Romberg:
Rapid Grassmannian Averaging with Chebyshev Polynomials. CoRR abs/2410.08956 (2024) - [i56]Daqian Bao, Alex Saad-Falcon, Justin Romberg:
Radon Implicit Field Transform (RIFT): Learning Scenes from Radar Signals. CoRR abs/2410.19801 (2024) - 2023
- [j56]Coleman DeLude, Rakshith Sharma Srinivasa, Santhosh Karnik, Christopher Hood, Mark A. Davenport, Justin Romberg:
Iterative Broadband Source Localization. IEEE J. Sel. Areas Inf. Theory 4: 453-469 (2023) - [j55]Sihan Zeng, Thinh T. Doan, Justin Romberg:
Finite-Time Convergence Rates of Decentralized Stochastic Approximation With Applications in Multi-Agent and Multi-Task Learning. IEEE Trans. Autom. Control. 68(5): 2758-2773 (2023) - [j54]Sajad Khodadadian, Thinh T. Doan, Justin Romberg, Siva Theja Maguluri:
Finite-Sample Analysis of Two-Time-Scale Natural Actor-Critic Algorithm. IEEE Trans. Autom. Control. 68(6): 3273-3284 (2023) - [j53]Andrew D. McRae, Justin Romberg, Mark A. Davenport:
Optimal Convex Lifted Sparse Phase Retrieval and PCA With an Atomic Matrix Norm Regularizer. IEEE Trans. Inf. Theory 69(3): 1866-1882 (2023) - [c87]Sudarshan Sharma, Wei Chun Wang, Coleman DeLude, Minah Lee, Nael Mizanur Rahman, Narasimha Vasishta Kidambi, Justin Romberg, Saibal Mukhopadhyay:
AFE-CIM: A Current-Domain Compute-In-Memory Macro for Analog-to-Feature Extraction. ESSCIRC 2023: 33-36 - [c86]Jihui Jin, Etienne Ollivier, Richard Touret, Matthew McKinley, Karim Sabra, Justin Romberg:
PETAL: Physics Emulation Through Averaged Linearizations for Solving Inverse Problems. NeurIPS 2023 - [c85]Sihan Zeng, Thinh T. Doan, Justin Romberg:
Connected Superlevel Set in (Deep) Reinforcement Learning and its Application to Minimax Theorems. NeurIPS 2023 - [i55]Sihan Zeng, Thinh T. Doan, Justin Romberg:
Connected Superlevel Set in (Deep) Reinforcement Learning and its Application to Minimax Theorems. CoRR abs/2303.12981 (2023) - [i54]Styliani I. Kampezidou, Justin Romberg, Kyriakos G. Vamvoudakis, Dimitri N. Mavris:
Scalable Online Learning of Approximate Stackelberg Solutions in Energy Trading Games with Demand Response Aggregators. CoRR abs/2304.02086 (2023) - [i53]Jihui Jin, Etienne Ollivier, Richard Touret, Matthew McKinley, Karim G. Sabra, Justin K. Romberg:
PETAL: Physics Emulation Through Averaged Linearizations for Solving Inverse Problems. CoRR abs/2305.11056 (2023) - 2022
- [j52]Santhosh Karnik, Justin Romberg, Mark A. Davenport:
Thomson's Multitaper Method Revisited. IEEE Trans. Inf. Theory 68(7): 4864-4891 (2022) - [j51]Tomer Hamam, Justin Romberg:
Streaming Solutions for Time-Varying Optimization Problems. IEEE Trans. Signal Process. 70: 3582-3597 (2022) - [c84]Tatsuya Miyano, Justin Romberg, Magnus Egerstedt:
Distributed Optimal Assignment Algorithm for Collective Foraging. ACC 2022: 4713-4720 - [c83]Tatsuya Miyano, Justin Romberg, Magnus Egerstedt:
Passivity-Based Distributed Control for Cooperative Unknown Payload Manipulation with Sensing/Actuation Delays. CCTA 2022: 319-326 - [c82]Sihan Zeng, Thinh T. Doan, Justin Romberg:
Finite-Time Complexity of Online Primal-Dual Natural Actor-Critic Algorithm for Constrained Markov Decision Processes. CDC 2022: 4028-4033 - [c81]Sheng Zhang, Ashwin Pananjady, Justin Romberg:
A Dual Accelerated Method for a Class of Distributed Optimization Problems: From Consensus to Decentralized Policy Evaluation. CDC 2022: 5220-5225 - [c80]Sihan Zeng, Thinh T. Doan, Justin Romberg:
Regularized Gradient Descent Ascent for Two-Player Zero-Sum Markov Games. NeurIPS 2022 - [i52]Sihan Zeng, Thinh T. Doan, Justin Romberg:
Regularized Gradient Descent Ascent for Two-Player Zero-Sum Markov Games. CoRR abs/2205.13746 (2022) - [i51]Sheng Zhang, Ashwin Pananjady, Justin Romberg:
A Dual Accelerated Method for Online Stochastic Distributed Averaging: From Consensus to Decentralized Policy Evaluation. CoRR abs/2207.11425 (2022) - [i50]Peimeng Guan, Jihui Jin, Justin Romberg, Mark A. Davenport:
Loop Unrolled Shallow Equilibrium Regularizer (LUSER) - A Memory-Efficient Inverse Problem Solver. CoRR abs/2210.04987 (2022) - 2021
- [j50]Junyi Gao, Rakshith Sharma Srinivasa, Cheng Qian, Lucas M. Glass, Jeffrey Spaeder, Justin Romberg, Jimeng Sun, Cao Xiao:
STAN: spatio-temporal attention network for pandemic prediction using real-world evidence. J. Am. Medical Informatics Assoc. 28(4): 733-743 (2021) - [j49]Peter Lawrence Brown, Matthew R. O'Shaughnessy, Christopher Rozell, Justin Romberg, Michael P. Flynn:
A 17.8-MS/s Compressed Sensing Radar Accelerator Using a Spiking Neural Network. IEEE J. Solid State Circuits 56(3): 834-843 (2021) - [j48]Thinh T. Doan, Siva Theja Maguluri, Justin Romberg:
Finite-Time Performance of Distributed Temporal-Difference Learning with Linear Function Approximation. SIAM J. Math. Data Sci. 3(1): 298-320 (2021) - [j47]Thinh T. Doan, Siva Theja Maguluri, Justin Romberg:
Fast Convergence Rates of Distributed Subgradient Methods With Adaptive Quantization. IEEE Trans. Autom. Control. 66(5): 2191-2205 (2021) - [j46]Thinh T. Doan, Siva Theja Maguluri, Justin Romberg:
Convergence Rates of Distributed Gradient Methods Under Random Quantization: A Stochastic Approximation Approach. IEEE Trans. Autom. Control. 66(10): 4469-4484 (2021) - [j45]Foroozan Karimzadeh, Ningyuan Cao, Brian Crafton, Justin Romberg, Arijit Raychowdhury:
A Hardware-Friendly Approach Towards Sparse Neural Networks Based on LFSR-Generated Pseudo-Random Sequences. IEEE Trans. Circuits Syst. I Regul. Pap. 68(2): 751-764 (2021) - [c79]Styliani I. Kampezidou, Justin Romberg, Kyriakos G. Vamvoudakis, Dimitri N. Mavris:
Online Adaptive Learning in Energy Trading Stackelberg Games with Time-Coupling Constraints. ACC 2021: 718-723 - [c78]Sihan Zeng, Thinh T. Doan, Justin Romberg:
Finite-Time Analysis of Decentralized Stochastic Approximation with Applications in Multi-Agent and Multi-Task Learning. CDC 2021: 2641-2646 - [c77]Sihan Zeng, Malik Aqeel Anwar, Thinh T. Doan, Arijit Raychowdhury, Justin Romberg:
A decentralized policy gradient approach to multi-task reinforcement learning. UAI 2021: 1002-1012 - [i49]Sajad Khodadadian, Thinh T. Doan, Siva Theja Maguluri, Justin Romberg:
Finite Sample Analysis of Two-Time-Scale Natural Actor-Critic Algorithm. CoRR abs/2101.10506 (2021) - [i48]Santhosh Karnik, Justin Romberg, Mark A. Davenport:
Thomson's Multitaper Method Revisited. CoRR abs/2103.11586 (2021) - [i47]Sihan Zeng, Thinh T. Doan, Justin Romberg:
A Two-Time-Scale Stochastic Optimization Framework with Applications in Control and Reinforcement Learning. CoRR abs/2109.14756 (2021) - [i46]Sihan Zeng, Thinh T. Doan, Justin Romberg:
Finite-Time Complexity of Online Primal-Dual Natural Actor-Critic Algorithm for Constrained Markov Decision Processes. CoRR abs/2110.11383 (2021) - [i45]Brighton Ancelin, Sohail Bahmani, Justin Romberg:
Decentralized Feature-Distributed Optimization for Generalized Linear Models. CoRR abs/2110.15283 (2021) - 2020
- [j44]Muya Chang, Li-Hsiang Lin, Justin Romberg, Arijit Raychowdhury:
OPTIMO: A 65-nm 279-GOPS/W 16-b Programmable Spatial-Array Processor with On-Chip Network for Solving Distributed Optimizations via the Alternating Direction Method of Multipliers. IEEE J. Solid State Circuits 55(3): 629-638 (2020) - [j43]Rakshith Sharma Srinivasa, Mark A. Davenport, Justin Romberg:
Trading Beams for Bandwidth: Imaging with Randomized Beamforming. SIAM J. Imaging Sci. 13(1): 317-350 (2020) - [j42]Alireza Aghasi, Afshin Abdi, Justin Romberg:
Fast Convex Pruning of Deep Neural Networks. SIAM J. Math. Data Sci. 2(1): 158-188 (2020) - [j41]Shaojie Xu, Fei Wang, Hua Wang, Justin Romberg:
In-Field Performance Optimization for mm-Wave Mixed-Signal Doherty Power Amplifiers: A Bandit Approach. IEEE Trans. Circuits Syst. 67-I(12): 5302-5315 (2020) - [j40]Ali Ahmed, Justin Romberg:
Compressive Sampling of Ensembles of Correlated Signals. IEEE Trans. Inf. Theory 66(2): 1078-1098 (2020) - [c76]Rakshith Sharma Srinivasa, Mark A. Davenport, Justin Romberg:
Sample complexity bounds for localized sketching. AISTATS 2020: 3275-3284 - [c75]Tatsuya Miyano, Justin Romberg, Magnus Egerstedt:
Primal-Dual Gradient Dynamics for Cooperative Unknown Payload Manipulation without Communication. ACC 2020: 2061-2067 - [c74]Tatsuya Miyano, Justin Romberg, Magnus Egerstedt:
Distributed Force/Position Optimization Dynamics for Cooperative Unknown Payload Manipulation. CDC 2020: 5366-5373 - [c73]Peter Lawrence Brown, Matthew R. O'Shaughnessy, Christopher J. Rozell, Justin Romberg, Michael P. Flynn:
A 17.8MS/s Neural-Network Compressed Sensing Radar Processor in 16nm FinFET CMOS. CICC 2020: 1-4 - [c72]Foroozan Karimzadeh, Ningyuan Cao, Brian Crafton, Justin Romberg, Arijit Raychowdhury:
Hardware-Aware Pruning of DNNs using LFSR-Generated Pseudo-Random Indices. ISCAS 2020: 1-5 - [c71]Thinh T. Doan, Justin Romberg:
Finite-Time Performance of Distributed Two-Time-Scale Stochastic Approximation. L4DC 2020: 26-36 - [c70]Andrew D. McRae, Justin Romberg, Mark A. Davenport:
Sample complexity and effective dimension for regression on manifolds. NeurIPS 2020 - [i44]Rakshith Sharma Srinivasa, Mark A. Davenport, Justin Romberg:
Localized sketching for matrix multiplication and ridge regression. CoRR abs/2003.09097 (2020) - [i43]Thinh T. Doan, Lam M. Nguyen, Nhan H. Pham, Justin Romberg:
Finite-Time Analysis of Stochastic Gradient Descent under Markov Randomness. CoRR abs/2003.10973 (2020) - [i42]Sihan Zeng, Aqeel Anwar, Thinh T. Doan, Justin Romberg, Arijit Raychowdhury:
A Decentralized Policy Gradient Approach to Multi-task Reinforcement Learning. CoRR abs/2006.04338 (2020) - [i41]Andrew D. McRae, Justin Romberg, Mark A. Davenport:
Sample complexity and effective dimension for regression on manifolds. CoRR abs/2006.07642 (2020) - [i40]Rakshith Sharma Srinivasa, Cao Xiao, Lucas Glass, Justin Romberg, Jimeng Sun:
Fast Graph Attention Networks Using Effective Resistance Based Graph Sparsification. CoRR abs/2006.08796 (2020) - [i39]Junyi Gao, Rakshith Sharma Srinivasa, Cheng Qian, Lucas M. Glass, Jeffrey Spaeder, Justin Romberg, Jimeng Sun, Cao Xiao:
STAN: Spatio-Temporal Attention Network for Pandemic Prediction Using Real World Evidence. CoRR abs/2008.04215 (2020) - [i38]Sihan Zeng, Thinh T. Doan, Justin Romberg:
Finite-Time Analysis of Decentralized Stochastic Approximation with Applications in Multi-Agent and Multi-Task Learning. CoRR abs/2010.15088 (2020)
2010 – 2019
- 2019
- [j39]Sohail Bahmani, Justin Romberg:
Solving Equations of Random Convex Functions via Anchored Regression. Found. Comput. Math. 19(4): 813-841 (2019) - [j38]Kevin Beale, Jianbo Chen, Anthony Giljum, Kevin F. Kelly, Justin Romberg:
A Hardware Realization of Superresolution Combining Random Coding and Blurring. IEEE Trans. Computational Imaging 5(3): 366-380 (2019) - [c69]Thinh T. Doan, Justin Romberg:
Linear Two-Time-Scale Stochastic Approximation A Finite-Time Analysis. Allerton 2019: 399-406 - [c68]Tomer Hamam, Justin Romberg:
Second-Order Filtering Algorithm for Streaming Optimization Problems. CAMSAP 2019: 21-25 - [c67]Muya Chang, Li-Hsiang Lin, Justin Romberg, Arijit Raychowdhury:
Optimo: A 65Nm 270Mhz 143.2Mw Programmable Spatial-Array-Processor With A Hierarchical Multi-Cast On-Chip Network For Solving Distributed Optimizations. CICC 2019: 1-4 - [c66]Muya Chang, Samantak Gangopadhyay, Tomer Hamam, Justin Romberg, Arijit Raychowdhury:
Efficient Signal Reconstruction via Distributed Least Square Optimization on a Systolic FPGA Architecture. ICASSP 2019: 1493-1497 - [c65]Shaojie Xu, Sihan Zeng, Justin Romberg:
Fast Compressive Sensing Recovery Using Generative Models with Structured Latent Variables. ICASSP 2019: 2967-2971 - [c64]Thinh T. Doan, Siva Theja Maguluri, Justin Romberg:
Finite-Time Analysis of Distributed TD(0) with Linear Function Approximation on Multi-Agent Reinforcement Learning. ICML 2019: 1626-1635 - [c63]Rakshith Sharma Srinivasa, Kiryung Lee, Marius Junge, Justin Romberg:
Decentralized sketching of low rank matrices. NeurIPS 2019: 10101-10110 - [i37]Shaojie Xu, Sihan Zeng, Justin Romberg:
Fast Compressive Sensing Recovery Using Generative Models with Structured Latent Variables. CoRR abs/1902.06913 (2019) - [i36]Shaojie Xu, Anvesha Amaravati, Justin Romberg, Arijit Raychowdhury:
Appearance-based Gesture recognition in the compressed domain. CoRR abs/1903.00100 (2019) - [i35]Thinh T. Doan, Siva Theja Maguluri, Justin Romberg:
Finite-Time Performance of Distributed Temporal Difference Learning with Linear Function Approximation. CoRR abs/1907.12530 (2019) - [i34]Sohail Bahmani, Justin Romberg:
Convex Programming for Estimation in Nonlinear Recurrent Models. CoRR abs/1908.09915 (2019) - [i33]Pietro Pierpaoli, Thinh T. Doan, Justin Romberg, Magnus Egerstedt:
A Reinforcement Learning Framework for Sequencing Multi-Robot Behaviors. CoRR abs/1909.05731 (2019) - [i32]Kiryung Lee, Sohail Bahmani, Yonina C. Eldar, Justin Romberg:
Phase Retrieval of Low-Rank Matrices by Anchored Regression. CoRR abs/1910.11477 (2019) - [i31]Foroozan Karimzadeh, Ningyuan Cao, Brian Crafton, Justin Romberg, Arijit Raychowdhury:
Hardware-aware Pruning of DNNs using LFSR-Generated Pseudo-Random Indices. CoRR abs/1911.04468 (2019) - 2018
- [j37]Kiryung Lee, Felix Krahmer, Justin Romberg:
Spectral Methods for Passive Imaging: Nonasymptotic Performance and Robustness. SIAM J. Imaging Sci. 11(3): 2110-2164 (2018) - [j36]Zhihui Zhu, Santhosh Karnik, Mark A. Davenport, Justin Romberg, Michael B. Wakin:
The Eigenvalue Distribution of Discrete Periodic Time-Frequency Limiting Operators. IEEE Signal Process. Lett. 25(1): 95-99 (2018) - [j35]Anvesha Amaravati, Shaojie Xu, Justin Romberg, Arijit Raychowdhury:
A 130 nm 165 nJ/frame Compressed-Domain Smashed-Filter-Based Mixed-Signal Classifier for "In-Sensor" Analytics in Smart Cameras. IEEE Trans. Circuits Syst. II Express Briefs 65-II(3): 296-300 (2018) - [j34]Anvesha Amaravati, Shaojie Xu, Ningyuan Cao, Justin Romberg, Arijit Raychowdhury:
A Light-Powered Smart Camera With Compressed Domain Gesture Detection. IEEE Trans. Circuits Syst. Video Technol. 28(10): 3077-3085 (2018) - [j33]Alireza Aghasi, Justin Romberg:
Extracting the Principal Shape Components via Convex Programming. IEEE Trans. Image Process. 27(7): 3513-3528 (2018) - [j32]Kiryung Lee, Ning Tian, Justin Romberg:
Fast and Guaranteed Blind Multichannel Deconvolution Under a Bilinear System Model. IEEE Trans. Inf. Theory 64(7): 4792-4818 (2018) - [j31]Sohail Bahmani, Justin Romberg, Prasad Tetali:
Algebraic Connectivity Under Site Percolation in Finite Weighted Graphs. IEEE Trans. Netw. Sci. Eng. 5(2): 86-91 (2018) - [j30]Zhihui Zhu, Santhosh Karnik, Michael B. Wakin, Mark A. Davenport, Justin Romberg:
ROAST: Rapid Orthogonal Approximate Slepian Transform. IEEE Trans. Signal Process. 66(22): 5887-5901 (2018) - [c62]Thinh T. Doan, Siva Theja Maguluri, Justin Romberg:
On the Convergence of Distributed Subgradient Methods under Quantization. Allerton 2018: 567-574 - [c61]Rakshith Sharma Srinivasa, Mark A. Davenport, Justin Romberg:
Localized random projections with applications to coherent array imaging. Allerton 2018: 617-623 - [c60]Insik Yoon, Muya Chang, Kai Ni, Matthew Jerry, Samantak Gangopadhyay, Gus Henry Smith, Tomer Hamam, Vijayakrishan Narayanan, Justin Romberg, Shih-Lien Lu, Suman Datta, Arijit Raychowdhury:
A FeFET Based Processing-In-Memory Architecture for Solving Distributed Least-Square Optimizations. DRC 2018: 1-2 - [i30]Alireza Aghasi, Afshin Abdi, Justin Romberg:
Fast Convex Pruning of Deep Neural Networks. CoRR abs/1806.06457 (2018) - 2017
- [c59]Sohail Bahmani, Justin Romberg:
Phase Retrieval Meets Statistical Learning Theory: A Flexible Convex Relaxation. AISTATS 2017: 252-260 - [c58]Amaravati Anvesha, Shaojie Xu, Justin Romberg, Arijit Raychowdhury:
A 65nm compressive-sensing time-based ADC with embedded classification and INL-aware training for arrhythmia detection. BioCAS 2017: 1-4 - [c57]Shaojie Xu, Anvesha Amaravati, Justin Romberg, Arijit Raychowdhury:
Appearance-based gesture recognition in the compressed domain. ICASSP 2017: 1722-1726 - [c56]Zhihui Zhu, Santhosh Karnik, Michael B. Wakin, Mark A. Davenport, Justin K. Romberg:
Fast orthogonal approximations of sampled sinusoids and bandlimited signals. ICASSP 2017: 4511-4515 - [c55]Justin Romberg:
Sampling and reconstruction in the 21st century. ICASSP 2017: 6468-6472 - [c54]Kiryung Lee, Ning Tian, Justin Romberg:
Performance guarantees of spectral methods for passive sensing of multiple channels. DSP 2017: 1-5 - [c53]Alireza Aghasi, Afshin Abdi, Nam Nguyen, Justin Romberg:
Net-Trim: Convex Pruning of Deep Neural Networks with Performance Guarantee. NIPS 2017: 3177-3186 - [i29]Sohail Bahmani, Justin Romberg:
Anchored Regression: Solving Random Convex Equations via Convex Programming. CoRR abs/1702.05327 (2017) - [i28]Zhihui Zhu, Santhosh Karnik, Mark A. Davenport, Justin Romberg, Michael B. Wakin:
The Eigenvalue Distribution of Discrete Periodic Time-Frequency Limiting Operators. CoRR abs/1707.05344 (2017) - [i27]Kiryung Lee, Felix Krahmer, Justin Romberg:
Spectral Methods for Passive Imaging: Non-asymptotic Performance and Robustness. CoRR abs/1708.04343 (2017) - [i26]Zhihui Zhu, Santhosh Karnik, Michael B. Wakin, Mark A. Davenport, Justin Romberg:
ROAST: Rapid Orthogonal Approximate Slepian Transform. CoRR abs/1712.04613 (2017) - 2016
- [j29]Michael B. Wakin, Rémi Gribonval, Visa Koivunen, Justin K. Romberg, John Wright:
Introduction to the Issue on Structured Matrices in Signal and Data Processing. IEEE J. Sel. Top. Signal Process. 10(4): 605-607 (2016) - [j28]Mark A. Davenport, Justin K. Romberg:
An Overview of Low-Rank Matrix Recovery From Incomplete Observations. IEEE J. Sel. Top. Signal Process. 10(4): 608-622 (2016) - [c52]Santhosh Karnik, Zhihui Zhu, Michael B. Wakin, Justin K. Romberg, Mark A. Davenport:
Fast computations for approximation and compression in Slepian spaces. GlobalSIP 2016: 1359-1363 - [c51]Amaravati Anvesha, Shaojie Xu, Ningyuan Cao, Justin Romberg, Arijit Raychowdhury:
A Light-powered, "Always-On", Smart Camera with Compressed Domain Gesture Detection. ISLPED 2016: 118-123 - [i25]Mark A. Davenport, Justin K. Romberg:
An overview of low-rank matrix recovery from incomplete observations. CoRR abs/1601.06422 (2016) - [i24]Alireza Aghasi, Justin K. Romberg:
Object Learning and Convex Cardinal Shape Composition. CoRR abs/1602.07613 (2016) - [i23]Alireza Aghasi, Barmak Heshmat, Albert Redo-Sanchez, Justin K. Romberg, Ramesh Raskar:
Sweep Distortion Removal from THz Images via Blind Demodulation. CoRR abs/1604.03426 (2016) - [i22]Amaravati Anvesha, Shaojie Xu, Ningyuan Cao, Justin Romberg, Arijit Raychowdhury:
A Light-powered, Always-On, Smart Camera with Compressed Domain Gesture Detection. CoRR abs/1605.08313 (2016) - [i21]Sohail Bahmani, Justin Romberg:
Phase Retrieval Meets Statistical Learning Theory: A Flexible Convex Relaxation. CoRR abs/1610.04210 (2016) - [i20]Alireza Aghasi, Nam Nguyen, Justin Romberg:
Net-Trim: A Layer-wise Convex Pruning of Deep Neural Networks. CoRR abs/1611.05162 (2016) - [i19]Sohail Bahmani, Justin K. Romberg, Prasad Tetali:
Algebraic Connectivity Under Site Percolation in Finite Weighted Graphs. CoRR abs/1612.05986 (2016) - 2015
- [j27]Sohail Bahmani, Justin K. Romberg:
Lifting for Blind Deconvolution in Random Mask Imaging: Identifiability and Convex Relaxation. SIAM J. Imaging Sci. 8(4): 2203-2238 (2015) - [j26]Alireza Aghasi, Justin K. Romberg:
Convex Cardinal Shape Composition. SIAM J. Imaging Sci. 8(4): 2887-2950 (2015) - [j25]Sohail Bahmani, Justin Romberg:
Compressive Deconvolution in Random Mask Imaging. IEEE Trans. Computational Imaging 1(4): 236-246 (2015) - [j24]Ali Ahmed, Justin K. Romberg:
Compressive Multiplexing of Correlated Signals. IEEE Trans. Inf. Theory 61(1): 479-498 (2015) - [j23]Aurele Balavoine, Christopher J. Rozell, Justin K. Romberg:
Discrete and Continuous-Time Soft-Thresholding for Dynamic Signal Recovery. IEEE Trans. Signal Process. 63(12): 3165-3176 (2015) - [c50]Alireza Aghasi, Justin K. Romberg:
Convex cardinal shape composition and object recognition in computer vision. ACSSC 2015: 1541-1545 - [c49]Sohail Bahmani, Justin K. Romberg:
Sketching for simultaneously sparse and low-rank covariance matrices. CAMSAP 2015: 357-360 - [c48]Sohail Bahmani, Justin K. Romberg:
Efficient Compressive Phase Retrieval with Constrained Sensing Vectors. NIPS 2015: 523-531 - [i18]Sohail Bahmani, Justin K. Romberg:
Lifting for Blind Deconvolution in Random Mask Imaging: Identifiability and Convex Relaxation. CoRR abs/1501.00046 (2015) - [i17]Ali Ahmed, Justin K. Romberg:
Compressive Sampling of Ensembles of Correlated Signals. CoRR abs/1501.06654 (2015) - [i16]Sohail Bahmani, Justin K. Romberg:
Near-Optimal Estimation of Simultaneously Sparse and Low-Rank Matrices from Nested Linear Measurements. CoRR abs/1506.08159 (2015) - [i15]Sohail Bahmani, Justin K. Romberg:
Efficient Compressive Phase Retrieval with Constrained Sensing Vectors. CoRR abs/1507.08254 (2015) - [i14]Sohail Bahmani, Justin K. Romberg:
Sketching for Simultaneously Sparse and Low-Rank Covariance Matrices. CoRR abs/1510.01670 (2015) - 2014
- [j22]Ali Ahmed, Benjamin Recht, Justin K. Romberg:
Blind Deconvolution Using Convex Programming. IEEE Trans. Inf. Theory 60(3): 1711-1732 (2014) - [j21]Aurele Balavoine, Justin K. Romberg, Christopher J. Rozell:
Correction to "Convergence and Rate Analysis of Neural Networks for Sparse Approximation". IEEE Trans. Neural Networks Learn. Syst. 25(8): 1595-1596 (2014) - [j20]Christopher K. Turnes, Doru Balcan, Justin K. Romberg:
Superfast Tikhonov Regularization of Toeplitz Systems. IEEE Trans. Signal Process. 62(15): 3809-3821 (2014) - [j19]M. Salman Asif, Justin K. Romberg:
Sparse Recovery of Streaming Signals Using ℓ1-Homotopy. IEEE Trans. Signal Process. 62(16): 4209-4223 (2014) - [c47]Xinyue Shen, Justin K. Romberg, Yuantao Gu:
Robust off-grid recovery from compressed measurements. ICASSP 2014: 3355-3359 - [c46]Aurele Balavoine, Christopher J. Rozell, Justin K. Romberg:
Iterative soft-thresholding for time-varying signal recovery. ICASSP 2014: 4958-4962 - [c45]Jiwei Huang, Sen Yang, Ashwin Lall, Justin K. Romberg, Jun (Jim) Xu, Chuang Lin:
Error estimating codes for insertion and deletion channels. SIGMETRICS 2014: 381-393 - [i13]William Mantzel, Justin K. Romberg:
Compressed Subspace Matching on the Continuum. CoRR abs/1407.5234 (2014) - [i12]Sohail Bahmani, Justin K. Romberg:
Compressive Deconvolution in Random Mask Imaging. CoRR abs/1412.7890 (2014) - 2013
- [j18]Alireza Aghasi, Justin K. Romberg:
Sparse Shape Reconstruction. SIAM J. Imaging Sci. 6(4): 2075-2108 (2013) - [j17]Armin Eftekhari, Justin K. Romberg, Michael B. Wakin:
Matched Filtering From Limited Frequency Samples. IEEE Trans. Inf. Theory 59(6): 3475-3496 (2013) - [j16]Aurele Balavoine, Christopher J. Rozell, Justin K. Romberg:
Convergence Speed of a Dynamical System for Sparse Recovery. IEEE Trans. Signal Process. 61(17): 4259-4269 (2013) - [j15]Muhammad Salman Asif, Justin K. Romberg:
Fast and Accurate Algorithms for Re-Weighted ℓ1-Norm Minimization. IEEE Trans. Signal Process. 61(23): 5905-5916 (2013) - [c44]M. Salman Asif, Felix Fernandes, Justin K. Romberg:
Low-complexity video compression and compressive sensing. ACSSC 2013: 579-583 - [c43]Ali Ahmed, Justin K. Romberg:
Compressive sampling in array processing. CAMSAP 2013: 192-195 - [c42]Alireza Aghasi, Sohail Bahmani, Justin K. Romberg:
A tightest convex envelope heuristic to row sparse and rank one matrices. GlobalSIP 2013: 627 - [c41]Han Lun Yap, Aurele Balavoine, William Mantzel, Ning Tian, Darryl Sale, Alireza Aghasi, Justin K. Romberg:
Poutine: A correlation estimator for ergodic stationary signals. ICASSP 2013: 6397-6401 - [c40]Aurele Balavoine, Christopher J. Rozell, Justin K. Romberg:
Convergence of a neural network for sparse approximation using the nonsmooth Łojasiewicz inequality. IJCNN 2013: 1-8 - [i11]Alireza Aghasi, Justin K. Romberg:
Sparse Shape Reconstruction. CoRR abs/1303.0018 (2013) - [i10]Muhammad Salman Asif, Justin K. Romberg:
Sparse Recovery of Streaming Signals Using L1-Homotopy. CoRR abs/1306.3331 (2013) - [i9]Ali Ahmed, Justin K. Romberg:
Compressive Multiplexing of Correlated Signals. CoRR abs/1308.5146 (2013) - 2012
- [j14]Michael B. Wakin, Stephen Becker, Eric B. Nakamura, Michael C. Grant, Emilio A. Sovero, Daniel Ching, Juhwan Yoo, Justin K. Romberg, Azita Emami-Neyestanak, Emmanuel J. Candès:
A Nonuniform Sampler for Wideband Spectrally-Sparse Environments. IEEE J. Emerg. Sel. Topics Circuits Syst. 2(3): 516-529 (2012) - [j13]Juhwan Yoo, Christopher K. Turnes, Eric B. Nakamura, Chi K. Le, Stephen Becker, Emilio A. Sovero, Michael B. Wakin, Michael C. Grant, Justin K. Romberg, Azita Emami-Neyestanak, Emmanuel J. Candès:
A Compressed Sensing Parameter Extraction Platform for Radar Pulse Signal Acquisition. IEEE J. Emerg. Sel. Topics Circuits Syst. 2(3): 626-638 (2012) - [j12]Christopher K. Turnes, Justin K. Romberg:
Efficient Calculations of 3-D FFTs on Spiral Contours. J. Sci. Comput. 50(3): 610-628 (2012) - [j11]Aurele Balavoine, Justin K. Romberg, Christopher J. Rozell:
Convergence and Rate Analysis of Neural Networks for Sparse Approximation. IEEE Trans. Neural Networks Learn. Syst. 23(9): 1377-1389 (2012) - [c39]Darryl Sale, Christopher J. Rozell, Justin K. Romberg, Aaron D. Lanterman:
Compressive ladar detector noise performance. ACSCC 2012: 416-420 - [c38]Ali Ahmed, Justin K. Romberg:
Compressive multiplexers for correlated signals. ACSCC 2012: 963-967 - [c37]Christopher K. Turnes, Doru Balcan, Justin K. Romberg:
Image deconvolution via superfast inversion of a class of two-level Toeplitz matrices. ICIP 2012: 3073-3076 - [c36]Darryl Sale, Christopher J. Rozell, Justin K. Romberg, Aaron D. Lanterman:
Compressive LADAR in realistic environments. SSP 2012: 720-723 - [i8]Muhammad Salman Asif, Justin K. Romberg:
Fast and Accurate Algorithms for Re-Weighted L1-Norm Minimization. CoRR abs/1208.0651 (2012) - [i7]Ali Ahmed, Benjamin Recht, Justin K. Romberg:
Blind Deconvolution using Convex Programming. CoRR abs/1211.5608 (2012) - 2011
- [c35]Ali Ahmed, Justin K. Romberg:
Compressive sampling of correlated signals. ACSCC 2011: 1188-1192 - [c34]Adam S. Charles, Muhammad Salman Asif, Justin K. Romberg, Christopher J. Rozell:
Sparsity penalties in dynamical system estimation. CISS 2011: 1-6 - [c33]Muhammad Salman Asif, Adam S. Charles, Justin K. Romberg, Christopher J. Rozell:
Estimation and dynamic updating of time-varying signals with sparse variations. ICASSP 2011: 3908-3911 - [i6]Armin Eftekhari, Justin K. Romberg, Michael B. Wakin:
Matched Filtering from Limited Frequency Samples. CoRR abs/1101.2713 (2011) - [i5]William Mantzel, Justin K. Romberg, Karim Sabra:
Compressive Matched-Field Processing. CoRR abs/1109.0318 (2011) - 2010
- [j10]Muhammad Salman Asif, Justin K. Romberg:
Dynamic Updating for ell1 Minimization. IEEE J. Sel. Top. Signal Process. 4(2): 421-434 (2010) - [j9]Ryan W. Robucci, Jordan D. Gray, Leung Kin Chiu, Justin K. Romberg, Paul E. Hasler:
Compressive Sensing on a CMOS Separable-Transform Image Sensor. Proc. IEEE 98(6): 1089-1101 (2010) - [j8]Joel A. Tropp, Jason N. Laska, Marco F. Duarte, Justin K. Romberg, Richard G. Baraniuk:
Beyond Nyquist: efficient sampling of sparse bandlimited signals. IEEE Trans. Inf. Theory 56(1): 520-544 (2010) - [c32]Justin K. Romberg:
An overview of recent results on the identification of sparse channels using random probes. CDC 2010: 2936-2941 - [c31]William Mantzel, Justin K. Romberg, Karim Sabra:
Randomized group testing for acoustic source localization. Computational Imaging 2010: 753309 - [c30]Muhammad Salman Asif, Justin K. Romberg:
On the LASSO and Dantzig selector equivalence. CISS 2010: 1-6 - [c29]Christopher K. Turnes, Justin K. Romberg:
Spiral FFT: An efficient method for 3-D FFTS on spiral MRI contours. ICIP 2010: 617-620 - [c28]William Mantzel, Justin K. Romberg:
Functional vanishing point estimation via a filtered-Radon operator. ICIP 2010: 1625-1628 - [c27]Nan Hua, Ashwin Lall, Justin K. Romberg, Jun (Jim) Xu, Mustafa al'Absi, Emre Ertin, Santosh Kumar, Shikhar Suri:
Just-in-time sampling and pre-filtering for wearable physiological sensors: going from days to weeks of operation on a single charge. Wireless Health 2010: 54-63 - [i4]Holger Rauhut, Justin K. Romberg, Joel A. Tropp:
Restricted Isometries for Partial Random Circulant Matrices. CoRR abs/1010.1847 (2010)
2000 – 2009
- 2009
- [j7]Justin K. Romberg:
Compressive Sensing by Random Convolution. SIAM J. Imaging Sci. 2(4): 1098-1128 (2009) - [c26]M. Salman Asif, William Mantzel, Justin Romberg:
Random channel coding and blind deconvolution. Allerton 2009: 1021-1025 - [c25]Muhammad Salman Asif, Justin K. Romberg:
Dantzig selector homotopy with dynamic measurements. Computational Imaging 2009: 72460 - [c24]Muhammad Salman Asif, Justin K. Romberg:
Dynamic updating for sparse time varying signals. CISS 2009: 3-8 - [c23]Honggab Kim, Justin K. Romberg, Wayne H. Wolf:
Multi-camera tracking on a graph using Markov chain Monte Carlo. ICDSC 2009: 1-8 - [c22]Justin Romberg:
A uniform uncertainty principle for Gaussian circulant matrices. DPS 2009: 1-5 - [i3]Joel A. Tropp, Jason N. Laska, Marco F. Duarte, Justin K. Romberg, Richard G. Baraniuk:
Beyond Nyquist: Efficient Sampling of Sparse Bandlimited Signals. CoRR abs/0902.0026 (2009) - [i2]Muhammad Salman Asif, Justin K. Romberg:
Dynamic updating for L1 minimization. CoRR abs/0903.1443 (2009) - [i1]Muhammad Salman Asif, William Mantzel, Justin K. Romberg:
Channel Protection: Random Coding Meets Sparse Channels. CoRR abs/0908.4265 (2009) - 2008
- [j6]Justin Romberg:
Imaging via Compressive Sampling. IEEE Signal Process. Mag. 25(2): 14-20 (2008) - [c21]M. Salman Asif, Justin Romberg:
Streaming measurements in compressive sensing: ℓ1 filtering. ACSCC 2008: 1051-1058 - [c20]Justin K. Romberg:
The Dantzig selector and generalized thresholding. CISS 2008: 22-25 - [c19]Ali Cafer Gürbüz, James H. McClellan, Justin K. Romberg, Waymond R. Scott:
Compressive sensing of parameterized shapes in images. ICASSP 2008: 1949-1952 - [c18]Ryan W. Robucci, Leung Kin Chiu, Jordan D. Gray, Justin K. Romberg, Paul E. Hasler, David V. Anderson:
Compressive sensing on a CMOS separable transform image sensor. ICASSP 2008: 5125-5128 - [c17]William Mantzel, Justin K. Romberg:
Capturing light field textures for video coding. ICIP 2008: 1604-1607 - 2007
- [j5]Emmanuel J. Candès, Justin K. Romberg:
Errata for Quantitative Robust Uncertainty Principles and Optimally Sparse Decompositions. Found. Comput. Math. 7(4): 529-531 (2007) - [c16]Justin Romberg:
Variational methods for compressive sampling. Computational Imaging 2007: 64980J - 2006
- [j4]Emmanuel J. Candès, Justin K. Romberg:
Quantitative Robust Uncertainty Principles and Optimally Sparse Decompositions. Found. Comput. Math. 6(2): 227-254 (2006) - [j3]Michael B. Wakin, Justin K. Romberg, Hyeokho Choi, Richard G. Baraniuk:
Wavelet-domain approximation and compression of piecewise smooth images. IEEE Trans. Image Process. 15(5): 1071-1087 (2006) - [j2]Emmanuel J. Candès, Justin K. Romberg, Terence Tao:
Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information. IEEE Trans. Inf. Theory 52(2): 489-509 (2006) - [c15]Justin K. Romberg:
Sparse Signal Recovery via l1 Minimization. CISS 2006: 213-215 - [c14]Emmanuel J. Candès, Justin K. Romberg:
Encoding the \ell_p Ball from Limited Measurements. DCC 2006: 33-42 - [c13]Emmanuel J. Candès, Justin K. Romberg:
Robust Signal Recovery from Incomplete Observations. ICIP 2006: 1281-1284 - 2005
- [c12]Emmanuel J. Candès, Justin K. Romberg:
Signal recovery from random projections. Computational Imaging 2005: 76-86 - 2003
- [c11]Justin K. Romberg, Michael B. Wakin, Richard G. Baraniuk:
Approximation and compression of piecewise smooth images using a wavelet/wedgelet geometric model. ICIP (1) 2003: 49-52 - [c10]Justin K. Romberg, Michael B. Wakin, Richard G. Baraniuk:
Multiscale geometric image processing. VCIP 2003: 1265-1272 - 2002
- [c9]Michael B. Wakin, Justin K. Romberg, Hyeokho Choi, Richard G. Baraniuk:
Image Compression using an Efficient Edge Cartoon + Texture Model. DCC 2002: 43- - [c8]Justin K. Romberg, Michael B. Wakin, Hyeokho Choi, Richard G. Baraniuk:
Rate-distortion optimized image compression using wedgelets. ICIP (3) 2002: 237-240 - [c7]Justin K. Romberg, Michael B. Wakin, Richard G. Baraniuk:
Multiscale wedgelet image analysis: fast decompositions and modeling. ICIP (3) 2002: 585-588 - 2001
- [j1]Justin K. Romberg, Hyeokho Choi, Richard G. Baraniuk:
Bayesian tree-structured image modeling using wavelet-domain hidden Markov models. IEEE Trans. Image Process. 10(7): 1056-1068 (2001) - [c6]Kris Popat, Daniel H. Greene, Justin K. Romberg, Dan S. Bloomberg:
Adding linguistic constraints to document image decoding: comparing the iterated complete path and stack algorithms. Document Recognition and Retrieval 2001: 259-271 - [c5]Justin K. Romberg, Hyeokho Choi, Richard G. Baraniuk:
Multiscale edge grammars for complex wavelet transforms. ICIP (1) 2001: 614-617 - 2000
- [c4]Hyeokho Choi, Justin K. Romberg, Richard G. Baraniuk, Nick G. Kingsbury:
Hidden Markov tree modeling of complex wavelet transforms. ICASSP 2000: 133-136 - [c3]Justin K. Romberg, Hyeokho Choi, Richard G. Baraniuk, Nick G. Kingsbury:
Multiscale Classification Using Complex Wavelets and Hidden Markov Tree Models. ICIP 2000: 371-374 - [c2]Justin K. Romberg, Hyeokho Choi, Richard G. Baraniuk:
Bayesian Tree-Structured Image Modeling. SSIAI 2000: 232-236
1990 – 1999
- 1999
- [c1]Justin K. Romberg, Hyeokho Choi, Richard G. Baraniuk:
Bayesian Wavelet-Domain Image Modeling Using Hidden Markov Trees. ICIP (1) 1999: 158-162
Coauthor Index
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