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2020 – today
- 2024
[j9]Seonho Kim
, Sohail Bahmani, Kiryung Lee:
Max-Linear Regression by Convex Programming. IEEE Trans. Inf. Theory 70(3): 1897-1912 (2024)- 2021
- [j8]Sohail Bahmani, Kiryung Lee:
Low-Rank Matrix Estimation from Rank-One Projections by Unlifted Convex Optimization. SIAM J. Matrix Anal. Appl. 42(3): 1119-1147 (2021) - [i17]Seonho Kim, Sohail Bahmani, Kiryung Lee:
Max-Linear Regression by Scalable and Guaranteed Convex Programming. CoRR abs/2103.07020 (2021) - [i16]Brighton Ancelin, Sohail Bahmani, Justin Romberg:
Decentralized Feature-Distributed Optimization for Generalized Linear Models. CoRR abs/2110.15283 (2021) - 2020
- [i15]Sohail Bahmani, Kiryung Lee:
Low-Rank Matrix Estimation From Rank-One Projections by Unlifted Convex Optimization. CoRR abs/2004.02718 (2020)
2010 – 2019
- 2019
- [j7]Sohail Bahmani, Justin Romberg:
Solving Equations of Random Convex Functions via Anchored Regression. Found. Comput. Math. 19(4): 813-841 (2019) - [i14]Sohail Bahmani, Justin Romberg:
Convex Programming for Estimation in Nonlinear Recurrent Models. CoRR abs/1908.09915 (2019) - [i13]Kiryung Lee, Sohail Bahmani, Yonina C. Eldar, Justin Romberg:
Phase Retrieval of Low-Rank Matrices by Anchored Regression. CoRR abs/1910.11477 (2019) - 2018
- [j6]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) - [i12]Sohail Bahmani:
Estimation from Non-Linear Observations via Convex Programming with Application to Bilinear Regression. CoRR abs/1806.07307 (2018) - 2017
- [c8]Sohail Bahmani, Justin Romberg:
Phase Retrieval Meets Statistical Learning Theory: A Flexible Convex Relaxation. AISTATS 2017: 252-260 - [i11]Sohail Bahmani, Justin Romberg:
Anchored Regression: Solving Random Convex Equations via Convex Programming. CoRR abs/1702.05327 (2017) - 2016
- [j5]Sohail Bahmani, Petros T. Boufounos, Bhiksha Raj:
Learning Model-Based Sparsity via Projected Gradient Descent. IEEE Trans. Inf. Theory 62(4): 2092-2099 (2016) - [i10]Sohail Bahmani, Justin Romberg:
Phase Retrieval Meets Statistical Learning Theory: A Flexible Convex Relaxation. CoRR abs/1610.04210 (2016) - [i9]Sohail Bahmani, Justin K. Romberg, Prasad Tetali:
Algebraic Connectivity Under Site Percolation in Finite Weighted Graphs. CoRR abs/1612.05986 (2016) - 2015
- [j4]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) - [j3]Sohail Bahmani, Justin Romberg:
Compressive Deconvolution in Random Mask Imaging. IEEE Trans. Computational Imaging 1(4): 236-246 (2015) - [c7]Sohail Bahmani, Justin K. Romberg:
Sketching for simultaneously sparse and low-rank covariance matrices. CAMSAP 2015: 357-360 - [c6]Sohail Bahmani, Justin K. Romberg:
Efficient Compressive Phase Retrieval with Constrained Sensing Vectors. NIPS 2015: 523-531 - [i8]Sohail Bahmani, Justin K. Romberg:
Lifting for Blind Deconvolution in Random Mask Imaging: Identifiability and Convex Relaxation. CoRR abs/1501.00046 (2015) - [i7]Sohail Bahmani, Justin K. Romberg:
Near-Optimal Estimation of Simultaneously Sparse and Low-Rank Matrices from Nested Linear Measurements. CoRR abs/1506.08159 (2015) - [i6]Sohail Bahmani, Justin K. Romberg:
Efficient Compressive Phase Retrieval with Constrained Sensing Vectors. CoRR abs/1507.08254 (2015) - [i5]Sohail Bahmani, Justin K. Romberg:
Sketching for Simultaneously Sparse and Low-Rank Covariance Matrices. CoRR abs/1510.01670 (2015) - 2014
- [i4]Sohail Bahmani, Justin K. Romberg:
Compressive Deconvolution in Random Mask Imaging. CoRR abs/1412.7890 (2014) - 2013
- [j2]Sohail Bahmani, Bhiksha Raj, Petros T. Boufounos:
Greedy sparsity-constrained optimization. J. Mach. Learn. Res. 14(1): 807-841 (2013) - [c5]Alireza Aghasi, Sohail Bahmani, Justin K. Romberg:
A tightest convex envelope heuristic to row sparse and rank one matrices. GlobalSIP 2013: 627 - [i3]Sohail Bahmani, Petros T. Boufounos, Bhiksha Raj:
Robust 1-bit Compressive Sensing via Gradient Support Pursuit. CoRR abs/1304.6627 (2013) - 2012
- [c4]Shoou-I Yu, Zhongwen Xu, Duo Ding, Waito Sze, Francisco Vicente, Zhenzhong Lan, Yang Cai, Shourabh Rawat, Peter F. Schulam, Nisarga Markandaiah, Sohail Bahmani, Antonio Juárez, Wei Tong, Yi Yang, Susanne Burger, Florian Metze, Rita Singh, Bhiksha Raj, Richard M. Stern, Teruko Mitamura, Eric Nyberg, Lu Jiang, Qiang Chen, Lisa M. Brown, Ankur Datta, Quanfu Fan, Rogério Schmidt Feris, Shuicheng Yan, Alexander G. Hauptmann, Sharath Pankanti:
Informedia @TRECVID 2012. TRECVID 2012 - [i2]Sohail Bahmani, Petros T. Boufounos, Bhiksha Raj:
Learning Model-Based Sparsity via Projected Gradient Descent. CoRR abs/1209.1557 (2012) - 2011
- [c3]Sohail Bahmani, Petros Boufounos, Bhiksha Raj:
Greedy sparsity-constrained optimization. ACSCC 2011: 1148-1152 - [i1]Sohail Bahmani, Bhiksha Raj:
A Unifying Analysis of Projected Gradient Descent for $ell_p$-constrained Least Squares. CoRR abs/1107.4623 (2011) - 2010
- [j1]Sohail Bahmani, Ivan V. Bajic, Atousa Hajshirmohammadi:
Joint Decoding of Unequally Protected JPEG2000 Bitstreams and Reed-Solomon Codes. IEEE Trans. Image Process. 19(10): 2693-2704 (2010)
2000 – 2009
- 2009
- [c2]Sohail Bahmani, Ivan V. Bajic, Atousa Hajshirmohammadi:
Improved Joint Source-Channel Decoding of JPEG2000 Images and Reed-Solomon Codes. ICC 2009: 1-5 - 2008
- [c1]Sohail Bahmani, Ivan V. Bajic, Atousa Hajshirmohammadi:
Joint source-chanel decoding of JPEG2000 images with unequal loss protection. ICASSP 2008: 1365-1368
Coauthor Index
aka: Justin Romberg
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last updated on 2024-08-20 20:32 CEST by the dblp team
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