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Noisy pooled PCR for virus testing
Fast testing can help mitigate the coronavirus disease 2019 (COVID-19) pandemic. Despite
their accuracy for single sample analysis, infectious diseases diagnostic tools, like RT-PCR …
their accuracy for single sample analysis, infectious diseases diagnostic tools, like RT-PCR …
A robust parallel algorithm for combinatorial compressed sensing
It was shown in previous work that a vector x ER n with at most k<; n nonzeros can be
recovered from an expander sketch Ax in O (nnz (A) log k) operations via the parallel-I 0 …
recovered from an expander sketch Ax in O (nnz (A) log k) operations via the parallel-I 0 …
Performance trade-offs in multi-processor approximate message passing
We consider large-scale linear inverse problems in Bayesian settings. Our general
approach follows a recent line of work that applies the approximate message passing (AMP) …
approach follows a recent line of work that applies the approximate message passing (AMP) …
History: An efficient and robust algorithm for noisy 1-bit compressed sensing
We consider the problem of sparse signal recovery from 1-bit measurements. Due to the
noise present in the acquisition and transmission process, some quantized bits may be …
noise present in the acquisition and transmission process, some quantized bits may be …
Optimal trade-offs in multi-processor approximate message passing
We consider large-scale linear inverse problems in Bayesian settings. We follow a recent
line of work that applies the approximate message passing (AMP) framework to multi …
line of work that applies the approximate message passing (AMP) framework to multi …
Statistical physics and information theory perspectives on linear inverse problems
Many real-world problems in machine learning, signal processing, and communications
assume that an unknown vector $ x $ is measured by a matrix A, resulting in a vector $ y …
assume that an unknown vector $ x $ is measured by a matrix A, resulting in a vector $ y …
Compressed sensing for graph signals
A Tawfik - 2018 - repositum.tuwien.at
In this thesis we are going to tackle the problem of estimating a sparse graph signal with an
unknown frequency support set of known size K from a sampled noisy version. Not knowing …
unknown frequency support set of known size K from a sampled noisy version. Not knowing …
[ספר][B] Solving Large-Scale Inverse Problems via Approximate Message Passing and Optimization
Y Ma - 2017 - search.proquest.com
Page 1 ABSTRACT MA, YANTING. Solving Large-Scale Inverse Problems via Approximate
Message Passing and Optimization. (Under the direction of Dror Baron.) This work studies the …
Message Passing and Optimization. (Under the direction of Dror Baron.) This work studies the …
Compressed sensing recovery with Bayesian approximate message passing using empirical least squares estimation without an explicit prior
A Tajjar - 2017 - repositum.tuwien.at
Compressed Sensing (CS) is a signal processing technique that allows for high-quality
reconstruction of a source signal vector of dimension N from a number MN of linear …
reconstruction of a source signal vector of dimension N from a number MN of linear …
Minimax Compressed Sensing Reconstruction
Final Report: Minimax Compressed Sensing Reconstruction Page 1 Standard Form 298 (Rev
8/98) Prescribed by ANSI Std. Z39.18 Final Report 62483-CS-SR.25 919-549-4350 …
8/98) Prescribed by ANSI Std. Z39.18 Final Report 62483-CS-SR.25 919-549-4350 …