126 citations · 300 across the 23 of their papers we have counts for
17 papers · 1 filter
Entropic CLT for Order Statistics
Martina Cardone, Alex Dytso, Cynthia Rush
It is well known that central order statistics exhibit a central limit behavior and converge to a Gaussian distribution as the sample size grows. This paper strengthens this known…
Near-Optimal Coding for Many-user Multiple Access Channels
Kuan Hsieh, Cynthia Rush, Ramji Venkataramanan
This paper considers the Gaussian multiple-access channel (MAC) in the asymptotic regime where the number of users grows linearly with the code length. We propose efficient coding…
The Most Informative Order Statistic and its Application to Image Denoising
Alex Dytso, Martina Cardone, Cynthia Rush
We consider the problem of finding the subset of order statistics that contains the most information about a sample of random variables drawn independently from some known parametr…
Unsourced Random Access with Coded Compressed Sensing: Integrating AMP and Belief Propagation
Vamsi K. Amalladinne, Asit Kumar Pradhan, Cynthia Rush +2
Sparse regression codes with approximate message passing (AMP) decoding have gained much attention in recent times. The concepts underlying this coding scheme extend to unsourced r…
Measuring Dependencies of Order Statistics: An Information Theoretic Perspective
Alex Dytso, Martina Cardone, Cynthia Rush
Consider a random sample drawn independently and identically distributed from some known sampling distribution . Let $X_{(1)} \le X_{(2)} \le ... \le X_…
All-or-nothing statistical and computational phase transitions in sparse spiked matrix estimation
Jean Barbier, Nicolas Macris, Cynthia Rush
We determine statistical and computational limits for estimation of a rank-one matrix (the spike) corrupted by an additive gaussian noise matrix, in a sparse limit, where the under…
mmWave Channel Estimation via Approximate Message Passing with Side Information
Dror Baron, Cynthia Rush, Yavuz Yapici
This work considers millimeter-wave channel estimation in a setting where parameters of the underlying mmWave channels are varying dynamically over time and there is a single drift…
Capacity-achieving Spatially Coupled Sparse Superposition Codes with AMP Decoding
Cynthia Rush, Kuan Hsieh, Ramji Venkataramanan
Sparse superposition codes, also called sparse regression codes (SPARCs), are a class of codes for efficient communication over the AWGN channel at rates approaching the channel ca…
On Approximate Message Passing for Unsourced Access with Coded Compressed Sensing
Vamsi K. Amalladinne, Asit Kumar Pradhan, Cynthia Rush +2
Sparse regression codes with approximate message passing (AMP) decoding have gained much attention in recent times. The concepts underlying this coding scheme extend to unsourced a…
Analysis of Approximate Message Passing with Non-Separable Denoisers and Markov Random Field Priors
Yanting Ma, Cynthia Rush, Dror Baron
Approximate message passing (AMP) is a class of low-complexity, scalable algorithms for solving high-dimensional linear regression tasks where one wishes to recover an unknown sign…
An Analysis of State Evolution for Approximate Message Passing with Side Information
Hangjin Liu, Cynthia Rush, Dror Baron
A common goal in many research areas is to reconstruct an unknown signal x from noisy linear measurements. Approximate message passing (AMP) is a class of low-complexity algorithms…
An Approximate Message Passing Framework for Side Information
Anna Ma, You, Zhou +3
Approximate message passing (AMP) methods have gained recent traction in sparse signal recovery. Additional information about the signal, or \emph{side information} (SI), is common…
Spatially Coupled Sparse Regression Codes: Design and State Evolution Analysis
Kuan Hsieh, Cynthia Rush, Ramji Venkataramanan
We consider the design and analysis of spatially coupled sparse regression codes (SC-SPARCs), which were recently introduced by Barbier et al. for efficient communication over the…
The Error Probability of Sparse Superposition Codes with Approximate Message Passing Decoding
Cynthia Rush, Ramji Venkataramanan
Sparse superposition codes, or sparse regression codes (SPARCs), are a recent class of codes for reliable communication over the AWGN channel at rates approaching the channel capac…
Analysis of Approximate Message Passing with a Class of Non-Separable Denoisers
Yanting Ma, Cynthia Rush, Dror Baron
Approximate message passing (AMP) is a class of efficient algorithms for solving high-dimensional linear regression tasks where one wishes to recover an unknown signal β_0 from noi…
Finite Sample Analysis of Approximate Message Passing Algorithms
Cynthia Rush, Ramji Venkataramanan
Approximate message passing (AMP) refers to a class of efficient algorithms for statistical estimation in high-dimensional problems such as compressed sensing and low-rank matrix e…
Capacity-achieving Sparse Superposition Codes via Approximate Message Passing Decoding
Cynthia Rush, Adam Greig, Ramji Venkataramanan
Sparse superposition codes were recently introduced by Barron and Joseph for reliable communication over the AWGN channel at rates approaching the channel capacity. The codebook is…