Search Results for author: Miguel R. D. Rodrigues

Found 25 papers, 5 papers with code

Robust lEarned Shrinkage-Thresholding (REST): Robust unrolling for sparse recover

no code implementations20 Oct 2021 Wei Pu, Chao Zhou, Yonina C. Eldar, Miguel R. D. Rodrigues

In this paper, we consider deep neural networks for solving inverse problems that are robust to forward model mis-specifications.

Compressive Sensing

Information-Theoretic Bounds on the Moments of the Generalization Error of Learning Algorithms

no code implementations3 Feb 2021 Gholamali Aminian, Laura Toni, Miguel R. D. Rodrigues

Generalization error bounds are critical to understanding the performance of machine learning models.

Blind Pareto Fairness and Subgroup Robustness

no code implementations1 Jan 2021 Natalia Martinez, Martin Bertran, Afroditi Papadaki, Miguel R. D. Rodrigues, Guillermo Sapiro

With the wide adoption of machine learning algorithms across various application domains, there is a growing interest in the fairness properties of such algorithms.

Fairness

Jensen-Shannon Information Based Characterization of the Generalization Error of Learning Algorithms

no code implementations23 Oct 2020 Gholamali Aminian, Laura Toni, Miguel R. D. Rodrigues

Generalization error bounds are critical to understanding the performance of machine learning models.

Image Separation with Side Information: A Connected Auto-Encoders Based Approach

no code implementations16 Sep 2020 Wei Pu, Barak Sober, Nathan Daly, Zahra Sabetsarvestani, Catherine Higgitt, Ingrid Daubechies, Miguel R. D. Rodrigues

These features are then used to (1) reproduce both of the original RGB images, (2) reconstruct the hypothetical separated X-ray images, and (3) regenerate the mixed X-ray image.

Model-Aware Regularization For Learning Approaches To Inverse Problems

no code implementations18 Jun 2020 Jaweria Amjad, Zhaoyan Lyu, Miguel R. D. Rodrigues

There are various inverse problems -- including reconstruction problems arising in medical imaging -- where one is often aware of the forward operator that maps variables of interest to the observations.

Lautum Regularization for Semi-supervised Transfer Learning

no code implementations2 Apr 2019 Daniel Jakubovitz, Miguel R. D. Rodrigues, Raja Giryes

We focus on the task of semi-supervised transfer learning, in which unlabeled samples from the target dataset are available during the network training on the source dataset.

Transfer Learning

Deep Learning for Inverse Problems: Bounds and Regularizers

no code implementations31 Jan 2019 Jaweria Amjad, Zhaoyan Lyu, Miguel R. D. Rodrigues

Inverse problems arise in a number of domains such as medical imaging, remote sensing, and many more, relying on the use of advanced signal and image processing approaches -- such as sparsity-driven techniques -- to determine their solution.

Image Super-Resolution

Generalization Error in Deep Learning

no code implementations3 Aug 2018 Daniel Jakubovitz, Raja Giryes, Miguel R. D. Rodrigues

Deep learning models have lately shown great performance in various fields such as computer vision, speech recognition, speech translation, and natural language processing.

Speech Recognition Translation

Multi-modal Image Processing based on Coupled Dictionary Learning

no code implementations26 Jun 2018 Pingfan Song, Miguel R. D. Rodrigues

In real-world scenarios, many data processing problems often involve heterogeneous images associated with different imaging modalities.

Denoising Dictionary Learning +1

Coupled Dictionary Learning for Multi-contrast MRI Reconstruction

1 code implementation26 Jun 2018 Pingfan Song, Lior Weizman, Joao F. C. Mota, Yonina C. Eldar, Miguel R. D. Rodrigues

In this paper, we propose a Coupled Dictionary Learning based multi-contrast MRI reconstruction (CDLMRI) approach to leverage an available guidance contrast to restore the target contrast.

Denoising Dictionary Learning +1

Multimodal Image Denoising based on Coupled Dictionary Learning

no code implementations26 Jun 2018 Pingfan Song, Miguel R. D. Rodrigues

The first stage performs joint sparse transform for multimodal images with respect to a group of learned coupled dictionaries, followed by a shrinkage operation on the sparse representations.

Dictionary Learning Image Denoising

Multimodal Image Super-resolution via Joint Sparse Representations induced by Coupled Dictionaries

1 code implementation25 Sep 2017 Pingfan Song, Xin Deng, João F. C. Mota, Nikos Deligiannis, Pier Luigi Dragotti, Miguel R. D. Rodrigues

This paper proposes a new approach to construct a high-resolution (HR) version of a low-resolution (LR) image given another HR image modality as reference, based on joint sparse representations induced by coupled dictionaries.

Dictionary Learning Image Super-Resolution

Learning to Succeed while Teaching to Fail: Privacy in Closed Machine Learning Systems

no code implementations23 May 2017 Jure Sokolic, Qiang Qiu, Miguel R. D. Rodrigues, Guillermo Sapiro

Confronted with this challenge, in this paper we open a new line of research, where the security, privacy, and fairness is learned and used in a closed environment.

Fairness

Generalization Error of Invariant Classifiers

no code implementations14 Oct 2016 Jure Sokolic, Raja Giryes, Guillermo Sapiro, Miguel R. D. Rodrigues

We show that whereas the generalization error of a non-invariant classifier is proportional to the complexity of the input space, the generalization error of an invariant classifier is proportional to the complexity of the base space.

Multi-modal dictionary learning for image separation with application in art investigation

no code implementations14 Jul 2016 Nikos Deligiannis, Joao F. C. Mota, Bruno Cornelis, Miguel R. D. Rodrigues, Ingrid Daubechies

Our dictionary learning framework can be tailored both to a single- and a multi-scale framework, with the latter leading to a significant performance improvement.

Dictionary Learning

Bounds on the Number of Measurements for Reliable Compressive Classification

no code implementations11 Jul 2016 Hugo Reboredo, Francesco Renna, Robert Calderbank, Miguel R. D. Rodrigues

This paper studies the classification of high-dimensional Gaussian signals from low-dimensional noisy, linear measurements.

Classification General Classification

Robust Large Margin Deep Neural Networks

no code implementations26 May 2016 Jure Sokolic, Raja Giryes, Guillermo Sapiro, Miguel R. D. Rodrigues

The generalization error of deep neural networks via their classification margin is studied in this work.

X-ray image separation via coupled dictionary learning

no code implementations20 May 2016 Nikos Deligiannis, João F. C. Mota, Bruno Cornelis, Miguel R. D. Rodrigues, Ingrid Daubechies

In support of art investigation, we propose a new source sepa- ration method that unmixes a single X-ray scan acquired from double-sided paintings.

Dictionary Learning

Classification and Reconstruction of High-Dimensional Signals from Low-Dimensional Features in the Presence of Side Information

no code implementations1 Dec 2014 Francesco Renna, Liming Wang, Xin Yuan, Jianbo Yang, Galen Reeves, Robert Calderbank, Lawrence Carin, Miguel R. D. Rodrigues

These conditions, which are reminiscent of the well-known Slepian-Wolf and Wyner-Ziv conditions, are a function of the number of linear features extracted from the signal of interest, the number of linear features extracted from the side information signal, and the geometry of these signals and their interplay.

General Classification

Compressed Sensing with Prior Information: Optimal Strategies, Geometry, and Bounds

2 code implementations22 Aug 2014 Joao F. C. Mota, Nikos Deligiannis, Miguel R. D. Rodrigues

Our bounds and geometrical interpretations reveal that if the prior information has good enough quality, L1-L1 minimization improves the performance of CS dramatically.

Information Theory Information Theory

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