Research
Research overview:
My main background is in information theory, high dimensional statistics and machine learning. Currently I am interested in a range of problems related to i) developing theoretically-founded computationally-efficient solutions to understand and address various issues rising in modern computational imaging, such as speckle noise and snapshot imaging, ii) online learning, iii) structure learning, and iv) developing an information theoretic understanding of neural networks and deep learning.
Journal Papers:
Bayesian denoising of structured sources and its implications on learning-based denoising
W. Zhou, J. Wabnig, S. Jalali, nformation and Inference: A Journal of IMA, 2023
Deep Unfolding for Snapshot Compressive Imaging
Z. Meng, X. Yuan, S Jalali, International Journal of Computer Vision, 2023
Compressed sensing in the presence of speckle noise
W. Zhou, S. Jalali, A. Maleki, IEEE Transactions on Information Theory, 2022
Using black-box compression algorithms for phase retrieval
M. Bakhshizade, A. Maleki, S. Jalali, IEEE Transactions on Information Theory, vol. 66, no. 12., p.p. 7978-8001, Dec. 2020. [arxiv]
Solving inverse problems via auto-encoders
P. Peng, S. Jalali and X. Yuan, IEEE Journal on Selected Areas in Information Theory, vol. 1, no. 1, pages 312-323, May 2020 [arxiv] [code]
Toward theoretically-founded learning-based compressed sensing
S. Jalali, IEEE Transactions on Information Theory, vol. 66 , no. 1, pages 387-400, Jan. 2020 [arxiv]
Snapshot compressed sensing: performance bounds and algorithms
S. Jalali, X. Yuan, IEEE Transactions on Information Theory,vol. 65, no. 12, pages 8005 - 8024 Dec. 2019 [arxiv]
Effect of backhaul constraints on uplink femtocell networks
Z. Zeinalpour-Yazdi, S. Jalali, H. V. Poor, IEEE Transactions on Vehicular Technology, vol. 67, no. 10, pages 9931-9946, Oct. 2018. [arxiv]
An efficient algorithm for compression-based compressed sensing
S. Beygi, S. Jalali, A. Maleki, U. Mitra, Information and Inference: A Journal of IMA, Aug. 2018 [arxiv]
New approach to Bayesian high-dimensional linear regression
S. Jalali, A. Maleki, Information and Inference: A Journal of IMA, vol. 7, no. 4, pp. 605-655, Dec. 2018 [arxiv]
Compression-based compressed sensing
F. Ebrahim-Rezagah, S. Jalali, E. Erkip, H. V. Poor, IEEE Transactions on Information Theory, vol. 63, no. 10, pp. 6735-6752, Oct. 2017 [arxiv]
Universal compressed sensing for almost lossless recovery
S. Jalali, H. V. Poor, IEEE Transactions on Information Theory, vol. 63, no. 5, pp. 2933 - 2953, May 2017 [arxiv]
From compression to compressed sensing
S. Jalali, and A. Maleki, Applied and Computational Harmonic Analysis (ACHA), vol. 40 (2), pp. 352-385, March 2016 [arxiv]
Separation of source-network coding and channel coding in wireline networks
S. Jalali. and M. Effros, IEEE Transactions on Information Theory, vol. 61, no. 4, April 2015. [arxiv]
Outage analysis of uplink two-tier networks
Z. Zeinalpour-Yazdi, S. Jalali, IEEE Transactions on Communications, vol. 62, no. 9, Sep. 2014 [arxiv]
Minimum complexity pursuit for universal compressed sensing
S. Jalali, A. Maleki, and R. Baraniuk, IEEE Transactions on Information Theory, vol. 60, no. 4, April 2014 [arxiv]
Block and sliding-block lossy compression via MCMC
S. Jalali, T. Weissman, IEEE Transactions on Communications, vol. 60, no. 8, August 2012.
Denoising via MCMC-based lossy compression
S. Jalali, T. Weissman, IEEE Transactions on Signal Processing, vol. 60, no. 6, June 2012.
Lossy compression of discrete sources via Viterbi algorithm
S. Jalali, A. Montanari, T. Weissman, IEEE Transactions on Information theory, vol. 58, no. 4, April 2012.
A universal scheme for Wyner-Ziv coding of discrete sources
S. Jalali, S. Verdú, T. Weissman, IEEE Transactions on Information theory, vol. 56, no. 4, pp. 1737-1750, April 2010.
Power control for multirate DS-CDMA systems with imperfect successive interference cancellation
S. Jalali, B.H. Khalaj, IEEE Transactions on Vehicular Technology, vol. 57, no. 1, Jan. 2008.
Conference Proceedings:
Efficient deep approximation of GMMs
S. Jalali, C. Nuzman, I. Saniee, Conference on Neural Information Processing Systems (NeurIPS), Vancouver, Canada, 2019 [arxiv] [poster]
Auto-encoders for compressed sensing
P. Peng, S. Jalali, X. Yuan, NeurIPS 2019 Workshop on Solving Inverse Problems with Deep Networks, Vancouver, Canada, 2019
Towards theoretically-founded learning-based denoising
W. Zhou, S. Jalali, IEEE International Symposium on Information Theory, Paris, France, 2019.
Solving linear inverse problems using generative models
S. Jalali, X. Yuan, IEEE International Symposium on Information Theory, Paris, France, 2019.
Towards clustering high-dimensional Gaussian mixture clouds in linear time
D. Kushnir, S. Jalali, I. Saniee, The 22nd International Conference on Artificial Intelligence and Statistics (AISTATS),
Compressive imaging via one-shot measurements
S. Jalali, X. Yuan, IEEE International Symposium on Information Theory, Vail, CO, 2018.
Compressive phase retrieval of structured signals
M. Bakhshizade, A. Maleki, S. Jalali, IEEE International Symposium on Information Theory, Vail, CO, 2018.
Compressed sensing of compressible signals
S. Beygi, S. Jalali, A. Maleki, U. Mitra, IEEE International Symposium on Information Theory, Aachen, Germany, 2017.
Minimum entropy pursuit: noise analysis
S. Jalali, H. V. Poor, IEEE International Conference on Acoustics, Speech and Signal Processing, New Orleans, 2017 (Invited session on Information-Theoretic Methods in Signal Acquisition, Analysis, and Processing).
Application of compression codes in compressed sensing
F. Ebrahim-Rezagah, S. Jalali, E. Erkip, H. V. Poor, Information Theory Workshop, Cambridge, UK, 2016.
Universal compressed sensing
S. Jalali, H. V. Poor, IEEE International Symposium on Information Theory, Barcelona, Spain, 2016.
Rate-distortion dimension of stochastic processes
F. Ebrahim-Rezagah, S. Jalali, E. Erkip, H. V. Poor, IEEE International Symposium on Information Theory, Barcelona, Spain, 2016. [arxiv]
Outage performance of uplink two-tier networks under backhaul constraint
S. Jalali, Z. Zeinalpour-Yazdi, H. V. Poor, International Conference on Communications, London, UK, 2015
Outage analysis of uplink open access two-tier networks
Z. Zeinalpour-Yazdi, S. Jalali, Iran Workshop on Communication and Information Theory (IWCIT), 2014.
From compression to compressed sensing: analog signals
A. Maleki, S. Jalali, Signal Processing with Adaptive Sparse Structured Representations, EPFL, Lausanne, 2013.
From compression to compressed sensing
S. Jalali, A. Maleki, IEEE International Symposium on Information Theory, Istanbul, Turkey, 2013.
On expected capacity of multicarrier frequency hopping systems
Z. Zeinalpour-Yazdi, S. Jalali, Iran Workshop on Communication and Information Theory (IWCIT), 2013.
Minimum complexity pursuit: stability analysis
S. Jalali, A. Maleki, and R. Baraniuk, IEEE International Symposium on Information Theory, Cambridge, MA, 2012. [arxiv]
Minimum complexity pursuit
S. Jalali, A. Maleki, Allerton Conference on Communication, Control and Computing, 2011. [arxiv]
On distortion bounds for dependent sources over wireless networks
S. Jalali, M. Effros, IEEE International Symposium on Information Theory, Saint Petersburg, Russia, 2011.
On the impact of a single edge on the network coding capacity
S. Jalali, M. Effros, and T. Ho, Information Theory and Applications (ITA), San Diego, CA, 2011. [arxiv]
Separation of network-source coding and channel coding in wireline networks
S. Jalali and M. Effros, Information Theory and Applications (ITA), San Diego, CA, 2011
On equivalence between network topologies
M. Effros, T. Ho and S. Jalali, Allerton Conference on Communication, Control and Computing, 2010. [arxiv]
On the separation of lossy source-network coding and channel coding in wireline networks
S. Jalali, M. Effros, IEEE International Symposium on Information Theory, Austin, Texas, 2010. [arxiv]
Multiple description coding of discrete ergodic sources
S. Jalali, and T. Weissman, Proc. of Allerton Conference on Communication, Control and Computing, 2009. [arxiv]
An iterative scheme for near optimal and universal lossy compression
S. Jalali, A. Montanari, T. Weissman, Information Theory Workshop (ITW), Volos, Greece, 2009. (invited paper)
An implementable scheme for universal lossy compression of discrete Markov sources
S. Jalali, A. Montanari, T. Weissman, Data Compression Conference (DCC), 2009. [arxiv]
Lossy coding via Markov chain Monte Carlo
S. Jalali, T. Weissman, IEEE International Symposium on Information Theory, Toronto, Canada, 2008. [arxiv]
Near optimal lossy source coding and compression-based denoising via Markov chain Monte Carlo
S. Jalali, T. Weissman, Conference on Information Sciences and Systems, Princeton, NJ, 2008. (invited paper)
Lossy source coding via Markov chain Monte Carlo
S. Jalali, T. Weissman, International Zurich Seminar on Communications, Zurich, 2008. (invited paper)
A universal Wyner-Ziv scheme for discrete sources
S. Jalali, S. Verdú, T. Weissman, Proc. IEEE International Symposium on Information Theory, Paris, France, 2007.
New bounds on the rate-distortion function of a binary Markov source
S. Jalali, T. Weissman, IEEE International Symposium on Information Theory, Paris, France, 2007.
Power management for multi-rate DS-CDMA systems with imperfect successive interference cancellation
S. Jalali, B. H. Khalaj, IEEE International Conference on Communications, Paris, France, 2004.
Ph.D. Dissertation: