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05/19/2023
Curve Your Enthusiasm: Concurvity Regularization in Differentiable Generalized Additive Models
Generalized Additive Models (GAMs) have recently experienced a resurgenc...
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11/18/2022
Let's Enhance: A Deep Learning Approach to Extreme Deblurring of Text Images
This work presents a novel deep-learning-based pipeline for the inverse ...
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02/07/2022
Gradient-Based Learning of Discrete Structured Measurement Operators for Signal Recovery
Countless signal processing applications include the reconstruction of s...
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07/31/2021
The Separation Capacity of Random Neural Networks
Neural networks with random weights appear in a variety of machine learn...
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06/01/2021
AAPM DL-Sparse-View CT Challenge Submission Report: Designing an Iterative Network for Fanbeam-CT with Unknown Geometry
This report is dedicated to a short motivation and description of our co...
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11/09/2020
Solving Inverse Problems With Deep Neural Networks – Robustness Included?
In the past five years, deep learning methods have become state-of-the-a...
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09/19/2020
A Unified Approach to Uniform Signal Recovery From Non-Linear Observations
Recent advances in quantized compressed sensing and high-dimensional est...
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09/07/2020
Compressed Sensing with 1D Total Variation: Breaking Sample Complexity Barriers via Non-Uniform Recovery (iTWIST'20)
This paper investigates total variation minimization in one spatial dime...
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04/11/2020
Generic Error Bounds for the Generalized Lasso with Sub-Exponential Data
This work performs a non-asymptotic analysis of the (constrained) genera...
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01/27/2020
Compressed Sensing with 1D Total Variation: Breaking Sample Complexity Barriers via Non-Uniform Recovery
This paper investigates total variation minimization in one spatial dime...
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08/20/2018
The Mismatch Principle: Statistical Learning Under Large Model Uncertainties
We study the learning capacity of empirical risk minimization with regar...
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04/13/2018
Robust 1-Bit Compressed Sensing via Hinge Loss Minimization
This work theoretically studies the problem of estimating a structured h...
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08/31/2016
A Mathematical Framework for Feature Selection from Real-World Data with Non-Linear Observations
In this paper, we study the challenge of feature selection based on a re...
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06/11/2015
