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09/12/2023
Optimization Guarantees of Unfolded ISTA and ADMM Networks With Smooth Soft-Thresholding
Solving linear inverse problems plays a crucial role in numerous applica...
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04/19/2023
Generalization and Estimation Error Bounds for Model-based Neural Networks
Model-based neural networks provide unparalleled performance for various...
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10/18/2022
Information-theoretic Characterizations of Generalization Error for the Gibbs Algorithm
Various approaches have been developed to upper bound the generalization...
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10/02/2022
Learning Algorithm Generalization Error Bounds via Auxiliary Distributions
Generalization error boundaries are essential for comprehending how well...
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06/29/2022
Theoretical Perspectives on Deep Learning Methods in Inverse Problems
In recent years, there have been significant advances in the use of deep...
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02/24/2022
An Information-theoretical Approach to Semi-supervised Learning under Covariate-shift
A common assumption in semi-supervised learning is that the labeled, unl...
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10/20/2021
Robust lEarned Shrinkage-Thresholding (REST): Robust unrolling for sparse recover
In this paper, we consider deep neural networks for solving inverse prob...
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07/28/2021
Characterizing the Generalization Error of Gibbs Algorithm with Symmetrized KL information
Bounding the generalization error of a supervised learning algorithm is ...
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02/03/2021
Information-Theoretic Bounds on the Moments of the Generalization Error of Learning Algorithms
Generalization error bounds are critical to understanding the performanc...
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10/23/2020
Jensen-Shannon Information Based Characterization of the Generalization Error of Learning Algorithms
Generalization error bounds are critical to understanding the performanc...
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09/16/2020
Image Separation with Side Information: A Connected Auto-Encoders Based Approach
X-radiography (X-ray imaging) is a widely used imaging technique in art ...
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06/18/2020
Model-Aware Regularization For Learning Approaches To Inverse Problems
There are various inverse problems – including reconstruction problems a...
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04/02/2019
Lautum Regularization for Semi-supervised Transfer Learning
Transfer learning is a very important tool in deep learning as it allows...
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01/31/2019
Deep Learning for Inverse Problems: Bounds and Regularizers
Inverse problems arise in a number of domains such as medical imaging, r...
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08/03/2018
Generalization Error in Deep Learning
Deep learning models have lately shown great performance in various fiel...
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07/22/2018
Hardware-Limited Task-Based Quantization
Quantization plays a critical role in digital signal processing systems....
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06/26/2018
Coupled Dictionary Learning for Multi-contrast MRI Reconstruction
Medical imaging tasks often involve multiple contrasts, such as T1- and ...
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06/26/2018
Multimodal Image Denoising based on Coupled Dictionary Learning
In this paper, we propose a new multimodal image denoising approach to a...
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06/26/2018
Multi-modal Image Processing based on Coupled Dictionary Learning
In real-world scenarios, many data processing problems often involve het...
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09/25/2017
Multimodal Image Super-Resolution via Joint Sparse Representations induced by Coupled Dictionaries
Real-world data processing problems often involve various image modaliti...
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05/23/2017
Learning to Succeed while Teaching to Fail: Privacy in Closed Machine Learning Systems
Security, privacy, and fairness have become critical in the era of data ...
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10/14/2016
Generalization Error of Invariant Classifiers
This paper studies the generalization error of invariant classifiers. In...
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07/14/2016
Multi-modal dictionary learning for image separation with application in art investigation
In support of art investigation, we propose a new source separation meth...
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07/11/2016
Bounds on the Number of Measurements for Reliable Compressive Classification
This paper studies the classification of high-dimensional Gaussian signa...
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05/26/2016
Robust Large Margin Deep Neural Networks
The generalization error of deep neural networks via their classificatio...
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05/20/2016
X-ray image separation via coupled dictionary learning
In support of art investigation, we propose a new source sepa- ration me...
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08/07/2015
Mismatch in the Classification of Linear Subspaces: Sufficient Conditions for Reliable Classification
This paper considers the classification of linear subspaces with mismatc...
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03/11/2015
Adaptive-Rate Sparse Signal Reconstruction With Application in Compressive Background Subtraction
We propose and analyze an online algorithm for reconstructing a sequence...
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12/01/2014
Classification and Reconstruction of High-Dimensional Signals from Low-Dimensional Features in the Presence of Side Information
This paper offers a characterization of fundamental limits on the classi...
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10/10/2014