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Gradient-Based Learning of Discrete Structured Measurement Operators for Signal Recovery
Jonathan Sauder, Martin Genzel, Peter Jung
Sub Mathematical Modeling
Mathematical Modeling
TU Berlin
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Dive into the research topics of 'Gradient-Based Learning of Discrete Structured Measurement Operators for Signal Recovery'. Together they form a unique fingerprint.
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Keyphrases
Signal Recovery
100%
Measurement Operator
100%
Gradient-based Learning
100%
Discrete Optimization
40%
Easy-to-implement
20%
Conventional Design
20%
Design Basis
20%
Computationally Efficient
20%
Optimization Task
20%
Linear Measurements
20%
Automatic Differentiation
20%
Signal Processing Applications
20%
Unrolled Optimization
20%
Gumbel
20%
Gradient Estimate
20%
Learned Measurement Matrix
20%
Iterative Recovery Algorithms
20%
Low Variance
20%
Categorical Random Variables
20%
Engineering
Tasks
100%
Measurement Matrix
100%
Random Variable ξ
100%
Randomization
100%
Signal Processing Application
100%
Computer Science
Measurement Operator
100%
Discrete Optimization
40%
Recovery Algorithm
20%
Optimization Task
20%
Underlying Hardware
20%
Matrix Measurement
20%
Linear Measurement
20%
Signal Processing Application
20%
Categorical Random Variable
20%
Reparametrization
20%