Underdetermined Anechoic Blind Source Separation via ellq-Basis-Pursuit With q<<1. - Rayan Saab; Özgür Yilmaz; Martin J. McKeown; Rafeef Abugharbieh (IEEE Trans. Signal Process., 2007)

Stable sparse approximations via nonconvex optimization. - Rayan Saab; Rick Chartrand; Özgür Yilmaz (ICASSP, 2008)

Sparse Recovery by Non-convex Optimization – Instance Optimality - Rayan Saab; Özgür Yilmaz (CoRR, 2008)

Algorithm 890: Sparco: A Testing Framework for Sparse Reconstruction. - Ewout van den Berg; Michael P. Friedlander; Gilles Hennenfent; Felix J. Herrmann; Rayan Saab; Özgür Yilmaz (ACM Trans. Math. Softw., 2009)

Sobolev duals of random frames. - C. Sinan Güntürk; Mark Lammers; Alexander M. Powell; Rayan Saab; Özgür Yilmaz (CISS, 2010)

Sigma delta quantization for compressed sensing. - C. Sinan Güntürk; Mark Lammers; Alexander M. Powell; Rayan Saab; Özgür Yilmaz (CISS, 2010)

Color image desaturation using sparse reconstruction. - Hassan Mansour; Rayan Saab; Panos Nasiopoulos; Rabab Kreidieh Ward (ICASSP, 2010)

Sobolev Duals for Random Frames and Sigma-Delta Quantization of Compressed Sensing Measurements - C. Sinan Güntürk; Alexander M. Powell; Rayan Saab; Özgür Yilmaz (CoRR, 2010)

Recovering Compressively Sampled Signals Using Partial Support Information. - Michael P. Friedlander; Hassan Mansour; Rayan Saab; Özgür Yilmaz (IEEE Trans. Inf. Theory, 2012)

Root-Exponential Accuracy for Coarse Quantization of Finite Frame Expansions. - Felix Krahmer; Rayan Saab; Rachel A. Ward (IEEE Trans. Inf. Theory, 2012)

Near-Optimal Encoding for Sigma-Delta Quantization of Finite Frame Expansions. - Mark A. Iwen; Rayan Saab (CoRR, 2013)

Sigma-Delta quantization of sub-Gaussian frame expansions and its application to compressed sensing. - Felix Krahmer; Rayan Saab; Özgür Yilmaz (CoRR, 2013)

Sobolev Duals for Random Frames and ΣΔ Quantization of Compressed Sensing Measurements. - C. Sinan Güntürk; Mark Lammers; Alexander M. Powell; Rayan Saab; Özgür Yilmaz (Found. Comput. Math., 2013)

Quantization and Compressive Sensing. - Petros T. Boufounos; Laurent Jacques; Felix Krahmer; Rayan Saab (CoRR, 2014)

Recovery Analysis for Weighted ℓ1-Minimization Using a Null Space Property. - Hassan Mansour; Rayan Saab (CoRR, 2014)

Near-Optimal Compression for Compressed Sensing. - Rayan Saab; Rongrong Wang; Özgür Yilmaz (DCC, 2015)

Weighted one-norm minimization with inaccurate support estimates: Sharp analysis via the null-space property. - Hassan Mansour; Rayan Saab (ICASSP, 2015)

Noise-shaping Quantization Methods for Frame-based and Compressive Sampling Systems. - Evan Chou; C. Sinan Güntürk; Felix Krahmer; Rayan Saab; Özgür Yilmaz (CoRR, 2015)

Quantization of compressive samples with stable and robust recovery. - Rayan Saab; Rongrong Wang; Özgür Yilmaz (CoRR, 2015)

A Deterministic Analysis of Decimation for Sigma-Delta Quantization of Bandlimited Functions. - Ingrid Daubechies; Rayan Saab (IEEE Signal Process. Lett., 2015)

Weighted ℓ1-Minimization for Sparse Recovery under Arbitrary Prior Information. - Deanna Needell; Rayan Saab; Tina Woolf (CoRR, 2016)

One-Bit Compressive Sensing With Norm Estimation. - Karin Knudson; Rayan Saab; Rachel A. Ward (IEEE Trans. Inf. Theory, 2016)

Simple Object Classification Using Binary Data. - Deanna Needell; Rayan Saab; Tina Woolf (AAAI Fall Symposia, 2017)

Quantized Compressed Sensing for Partial Random Circulant Matrices. - Joe-Mei Feng; Felix Krahmer; Rayan Saab (CoRR, 2017)

Quantization for Low-Rank Matrix Recovery. - Eric Lybrand; Rayan Saab (CoRR, 2017)

Fast binary embeddings, and quantized compressed sensing with structured matrices. - Thang Huynh; Rayan Saab (CoRR, 2018)

Simple Classification Using Binary Data. - Deanna Needell; Rayan Saab; Tina Woolf (J. Mach. Learn. Res., 2018)

From Compressed Sensing to Compressed Bit-Streams: Practical Encoders, Tractable Decoders. - Rayan Saab; Rongrong Wang; Özgür Yilmaz (IEEE Trans. Inf. Theory, 2018)

New Algorithms and Improved Guarantees for One-Bit Compressed Sensing on Manifolds. - Mark A. Iwen; Eric Lybrand; Aaron A. Nelson; Rayan Saab (CoRR, 2019)

Admissible Measurements and Robust Algorithms for Ptychography. - Brian Preskitt; Rayan Saab (CoRR, 2019)

Random Vector Functional Link Networks for Function Approximation on Manifolds. - Deanna Needell; Aaron A. Nelson; Rayan Saab; Palina Salanevich (CoRR, 2020)

A direct solver for the phase retrieval problem in ptychographic imaging. - Nada Sissouno; Florian Boßmann; Frank Filbir; Mark A. Iwen; Maik Kahnt; Rayan Saab; Christian Schroer; Wolfgang zu Castell (Math. Comput. Simul., 2020)

Faster Binary Embeddings for Preserving Euclidean Distances. - Jinjie Zhang; Rayan Saab (ICLR, 2021)

On the $ ell^ infty$-norms of the Singular Vectors of Arbitrary Powers of a Difference Matrix with Applications to Sigma-Delta Quantization. - Theodore Faust; Mark A. Iwen; Rayan Saab; Rongrong Wang (CoRR, 2021)

Sigma-Delta and Distributed Noise-Shaping Quantization Methods for Random Fourier Features. - Jinjie Zhang; Alexander Cloninger; Rayan Saab (CoRR, 2021)

On the Number of Faces and Radii of Cells Induced by Gaussian Spherical Tessellations. - Eric Lybrand; Anna Ma; Rayan Saab (CoRR, 2021)

A Greedy Algorithm for Quantizing Neural Networks. - Eric Lybrand; Rayan Saab (J. Mach. Learn. Res., 2021)

Spectrally Adaptive Common Spatial Patterns. - Mahta Mousavi; Eric Lybrand; Shuangquan Feng; Shuai Tang; Rayan Saab; Virginia de Sa (CoRR, 2022)

A simple approach for quantizing neural networks. - Johannes Maly; Rayan Saab (CoRR, 2022)

SPFQ: A Stochastic Algorithm and Its Error Analysis for Neural Network Quantization. - Jinjie Zhang; Rayan Saab (CoRR, 2023)

Post-training Quantization for Neural Networks with Provable Guarantees. - Jinjie Zhang; Yixuan Zhou; Rayan Saab (SIAM J. Math. Data Sci., 2023)

Accumulator-Aware Post-Training Quantization. - Ian Colbert; Fabian Grob; Giuseppe Franco; Jinjie Zhang; Rayan Saab (CoRR, 2024)

Unified Stochastic Framework for Neural Network Quantization and Pruning. - Haoyu Zhang; Rayan Saab (CoRR, 2024)

Random vector functional link networks for function approximation on manifolds. - Deanna Needell; Aaron A. Nelson; Rayan Saab; Palina Salanevich; Olov Schavemaker (Frontiers Appl. Math. Stat., 2024)

Corrigendum: Post-training Quantization for Neural Networks with Provable Guarantees. - Jinjie Zhang; Yixuan Zhou; Rayan Saab (SIAM J. Math. Data Sci., 2024)

Theoretical Guarantees for Low-Rank Compression of Deep Neural Networks. - Shihao Zhang; Rayan Saab (CoRR, 2025)

Qronos: Correcting the Past by Shaping the Future... in Post-Training Quantization. - Shihao Zhang; Haoyu Zhang; Ian Colbert; Rayan Saab (CoRR, 2025)

Provable Post-Training Quantization: Theoretical Analysis of OPTQ and Qronos. - Haoyu Zhang; Shihao Zhang; Ian Colbert; Rayan Saab (CoRR, 2025)