Galen Reeves

According to our database, Galen Reeves authored at least 54 papers between 2008 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Reed-Muller Codes on BMS Channels Achieve Vanishing Bit-Error Probability for all Rates Below Capacity.

Galen Reeves, Henry D. Pfister

IEEE Trans. Inf. Theory, February, 2024

Linear Operator Approximate Message Passing (OpAMP).

Riccardo Rossetti, Bobak Nazer, Galen Reeves

CoRR, 2024

Linear Operator Approximate Message Passing: Power Method with Partial and Stochastic Updates.

Riccardo Rossetti, Bobak Nazer, Galen Reeves

Proceedings of the IEEE International Symposium on Information Theory, 2024

2023

Approximate Message Passing for the Matrix Tensor Product Model.

Riccardo Rossetti, Galen Reeves

CoRR, 2023

Achieving Capacity on Non-Binary Channels with Generalized Reed-Muller Codes.

Galen Reeves, Henry D. Pfister

Proceedings of the IEEE International Symposium on Information Theory, 2023

2022

$k$-Sliced Mutual Information: A Quantitative Study of Scalability with Dimension.

Ziv Goldfeld, Kristjan H. Greenewald, Theshani Nuradha, Galen Reeves

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Fundamental limits for rank-one matrix estimation with groupwise heteroskedasticity.

Joshua K. Behne, Galen Reeves

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Gaussian Approximation of Quantization Error for Estimation From Compressed Data.

Alon Kipnis, Galen Reeves

IEEE Trans. Inf. Theory, 2021

Reed-Muller Codes Achieve Capacity on BMS Channels.

Galen Reeves, Henry D. Pfister

CoRR, 2021

Rank-one matrix estimation with groupwise heteroskedasticity.

Joshua K. Behne, Galen Reeves

CoRR, 2021

The Gaussian equivalence of generative models for learning with shallow neural networks.

Sebastian Goldt, Bruno Loureiro, Galen Reeves, Florent Krzakala, Marc Mézard, Lenka Zdeborová

Proceedings of the Mathematical and Scientific Machine Learning, 2021

Convergence of Gaussian-smoothed optimal transport distance with sub-gamma distributions and dependent samples.

Yixing Zhang, Xiuyuan Cheng, Galen Reeves

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Information-Theoretic Limits for the Matrix Tensor Product.

Galen Reeves

IEEE J. Sel. Areas Inf. Theory, 2020

A Two-Moment Inequality with Applications to Rényi Entropy and Mutual Information.

Galen Reeves

Entropy, 2020

The Gaussian equivalence of generative models for learning with two-layer neural networks.

Sebastian Goldt, Galen Reeves, Marc Mézard, Florent Krzakala, Lenka Zdeborová

CoRR, 2020

Information-theoretic limits of a multiview low-rank symmetric spiked matrix model.

Jean Barbier, Galen Reeves

Proceedings of the IEEE International Symposium on Information Theory, 2020

2019

The Replica-Symmetric Prediction for Random Linear Estimation With Gaussian Matrices Is Exact.

Galen Reeves, Henry D. Pfister

IEEE Trans. Inf. Theory, 2019

Understanding Phase Transitions via Mutual Information and MMSE.

Galen Reeves, Henry D. Pfister

CoRR, 2019

The Geometry of Community Detection via the MMSE Matrix.

Galen Reeves, Vaishakhi Mayya, Alexander Volfovsky

Proceedings of the IEEE International Symposium on Information Theory, 2019

Adversarially Learned Representations for Information Obfuscation and Inference.

Martín Bertrán, Natalia Martínez, Afroditi Papadaki, Qiang Qiu, Miguel R. D. Rodrigues, Galen Reeves, Guillermo Sapiro

Proceedings of the 36th International Conference on Machine Learning, 2019

The All-or-Nothing Phenomenon in Sparse Linear Regression.

Galen Reeves, Jiaming Xu, Ilias Zadik

Proceedings of the Conference on Learning Theory, 2019

All-or-Nothing Phenomena: From Single-Letter to High Dimensions.

Galen Reeves, Jiaming Xu, Ilias Zadik

Proceedings of the 8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2019

Gaussian Mixture Models for Stochastic Block Models with Non-Vanishing Noise.

Heather Mathews, Vaishakhi Mayya, Alexander Volfovsky, Galen Reeves

Proceedings of the 8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2019

Mutual Information in Community Detection with Covariate Information and Correlated Networks.

Vaishakhi Mayya, Galen Reeves

Proceedings of the 57th Annual Allerton Conference on Communication, 2019

2018

Mutual Information as a Function of Matrix SNR for Linear Gaussian Channels.

Galen Reeves, Henry D. Pfister, Alex Dytso

Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

Single Letter Formulas for Quantized Compressed Sensing with Gaussian Codebooks.

Alon Kipnis, Galen Reeves, Yonina C. Eldar

Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

2017

Conditional central limit theorems for Gaussian projections.

Galen Reeves

Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017

Two-moment inequalities for Rényi entropy and mutual information.

Galen Reeves

Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017

Compressed sensing under optimal quantization.

Alon Kipnis, Galen Reeves, Yonina C. Eldar, Andrea J. Goldsmith

Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017

A performance-based approach to designing the stimulus presentation paradigm for the P300-based BCI by exploiting coding theory.

B. O. Mainsah, Leslie M. Collins, Galen Reeves, Chandra S. Throckmorton

Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Decoupling in random linear estimation.

Galen Reeves, Harry Pfister

Proceedings of the 51st Annual Conference on Information Sciences and Systems, 2017

Additivity of information in multilayer networks via additive Gaussian noise transforms.

Galen Reeves

Proceedings of the 55th Annual Allerton Conference on Communication, 2017

2016

Classification and Reconstruction of High-Dimensional Signals From Low-Dimensional Features in the Presence of Side Information.

Francesco Renna, Liming Wang, Xin Yuan, Jianbo Yang, Galen Reeves, A. Robert Calderbank, Lawrence Carin, Miguel R. D. Rodrigues

IEEE Trans. Inf. Theory, 2016

The replica-symmetric prediction for compressed sensing with Gaussian matrices is exact.

Galen Reeves, Henry D. Pfister

Proceedings of the IEEE International Symposium on Information Theory, 2016

Modeling the P300-based brain-computer interface as a channel with memory.

Vaishakhi Mayya, Boyla Mainsah, Galen Reeves

Proceedings of the 54th Annual Allerton Conference on Communication, 2016

Information-theoretic analysis of refractory effects in the P300 speller.

Vaishakhi Mayya, Boyla Mainsah, Galen Reeves

Proceedings of the 50th Asilomar Conference on Signals, Systems and Computers, 2016

2015

Classification and reconstruction of compressed GMM signals with side information.

Francesco Renna, Liming Wang, Xin Yuan, Jianbo Yang, Galen Reeves, A. Robert Calderbank, Lawrence Carin, Miguel R. D. Rodrigues

Proceedings of the IEEE International Symposium on Information Theory, 2015

Quantifying uncertainty in variable selection with arbitrary matrices.

Willem van den Boom, David B. Dunson, Galen Reeves

Proceedings of the 6th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2015

2014

Classification and Reconstruction of High-Dimensional Signals from Low-Dimensional Noisy Features in the Presence of Side Information.

Francesco Renna, Liming Wang, Xin Yuan, Jianbo Yang, Galen Reeves, A. Robert Calderbank, Lawrence Carin, Miguel R. D. Rodrigues

CoRR, 2014

The fundamental limits of stable recovery in compressed sensing.

Galen Reeves

Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014

2013

Approximate Sparsity Pattern Recovery: Information-Theoretic Lower Bounds.

Galen Reeves, Michael Gastpar

IEEE Trans. Inf. Theory, 2013

The minimax noise sensitivity in compressed sensing.

Galen Reeves, David L. Donoho

Proceedings of the 2013 IEEE International Symposium on Information Theory, 2013

Achieving Bayes MMSE performance in the sparse signal + Gaussian white noise model when the noise level is unknown.

David L. Donoho, Galen Reeves

Proceedings of the 2013 IEEE International Symposium on Information Theory, 2013

Beyond sparsity: Universally stable compressed sensing when the number of 'free' values is less than the number of observations.

Galen Reeves

Proceedings of the 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2013

2012

The Sampling Rate-Distortion Tradeoff for Sparsity Pattern Recovery in Compressed Sensing.

Galen Reeves, Michael Gastpar

IEEE Trans. Inf. Theory, 2012

The sensitivity of compressed sensing performance to relaxation of sparsity.

David L. Donoho, Galen Reeves

Proceedings of the 2012 IEEE International Symposium on Information Theory, 2012

Compressed sensing phase transitions: Rigorous bounds versus replica predictions.

Galen Reeves, Michael Gastpar

Proceedings of the 46th Annual Conference on Information Sciences and Systems, 2012

2011

Sparsity Pattern Recovery in Compressed Sensing.

Galen Reeves

PhD thesis, 2011

A compressed sensing wire-tap channel.

Galen Reeves, Naveen Goela, Nebojsa Milosavljevic, Michael Gastpar

Proceedings of the 2011 IEEE Information Theory Workshop, 2011

On the role of diversity in sparsity estimation.

Galen Reeves, Michael Gastpar

Proceedings of the 2011 IEEE International Symposium on Information Theory Proceedings, 2011

2010

Fundamental Tradeoffs for Sparsity Pattern Recovery

Galen Reeves, Michael Gastpar

CoRR, 2010

"Compressed" compressed sensing.

Galen Reeves, Michael Gastpar

Proceedings of the IEEE International Symposium on Information Theory, 2010

2009

Managing Massive Time Series Streams with MultiScale Compressed Trickles.

Galen Reeves, Jie Liu, Suman Nath, Feng Zhao

Proc. VLDB Endow., 2009

2008

Sampling bounds for sparse support recovery in the presence of noise.

Galen Reeves, Michael Gastpar

Proceedings of the 2008 IEEE International Symposium on Information Theory, 2008