Miguel R. D. Rodrigues

ORCID

Publication Activity (10 Years)

Years Active: 2002-2024
Publications (10 Years): 114

Top Venues

CoRR

ICASSP

IEEE Trans. Signal Process.

ISIT

Publications

Zhaoyan Lyu, Gholamali Aminian, Miguel R. D. Rodrigues
Synthetic Labeling: A Novel Approach to Advancing Few-Shot Learning. Tiny Papers @ ICLR (2024)
Martin Ferianc, Ondrej Bohdal, Timothy M. Hospedales, Miguel R. D. Rodrigues
Navigating Noise: A Study of How Noise Influences Generalisation and Calibration of Neural Networks. Trans. Mach. Learn. Res. 2024 (2024)
Basheeruddin Shah Shaik, Pradyumna Pradhan, Wei Pu, Ramunaidu Randhi, Miguel R. D. Rodrigues, Yonina C. Eldar
Optimization Guarantees of Unfolded ISTA and ADMM Networks With Smooth Soft-Thresholding. IEEE Trans. Signal Process. 72 (2024)
Afroditi Papadaki, Natalia Martínez, Martín Bertrán, Guillermo Sapiro, Miguel R. D. Rodrigues
Federated Fairness without Access to Sensitive Groups. CoRR (2024)
Gholamali Aminian, Mohammad Saeed Masiha, Laura Toni, Miguel R. D. Rodrigues
Learning Algorithm Generalization Error Bounds via Auxiliary Distributions. IEEE J. Sel. Areas Inf. Theory 5 (2024)
Gholamali Aminian, Yuheng Bu, Laura Toni, Miguel R. D. Rodrigues, Gregory W. Wornell
Information-Theoretic Characterizations of Generalization Error for the Gibbs Algorithm. IEEE Trans. Inf. Theory 70 (1) (2024)
Yuheng Bu, Harsha Vardhan Tetali, Gholamali Aminian, Miguel R. D. Rodrigues, Gregory W. Wornell
On the Generalization Error of Meta Learning for the Gibbs Algorithm. CoRR (2023)
Shaik Basheeruddin Shah, Pradyumna Pradhan, Wei Pu, Ramunaidu Randhi, Miguel R. D. Rodrigues, Yonina C. Eldar
Optimization Guarantees of Unfolded ISTA and ADMM Networks With Smooth Soft-Thresholding. CoRR (2023)
Haiyun He, Gholamali Aminian, Yuheng Bu, Miguel R. D. Rodrigues, Vincent Y. F. Tan
How Does Pseudo-Labeling Affect the Generalization Error of the Semi-Supervised Gibbs Algorithm? AISTATS (2023)
Avner Shultzman, Eyar Azar, Miguel R. D. Rodrigues, Yonina C. Eldar
Generalization and Estimation Error Bounds for Model-based Neural Networks. ICLR (2023)
Chao Zhou, Zhaoyan Lyu, Miguel R. D. Rodrigues
BITS-Net: Blind Image Transparency Separation Network. ICIP (2023)
Daniel Jakubovitz, David Uliel, Miguel R. D. Rodrigues, Raja Giryes
An information-Theoretic Approach to Semi-supervised Transfer Learning. CoRR (2023)
Jialong Xu, Bo Ai, Wei Chen, Ning Wang, Miguel R. D. Rodrigues
Deep Joint Source-Channel Coding for Image Transmission With Visual Protection. IEEE Trans. Cogn. Commun. Netw. 9 (6) (2023)
Yuheng Bu, Harsha Vardhan Tetali, Gholamali Aminian, Miguel R. D. Rodrigues, Gregory W. Wornell
On the Generalization Error of Meta Learning for the Gibbs Algorithm. ISIT (2023)
Wei Pu, Barak Sober, Nathan Daly, Chao Zhou, Zahra Sabetsarvestani, Catherine Higgitt, Ingrid Daubechies, Miguel R. D. Rodrigues
Image Separation With Side Information: A Connected Auto-Encoders Based Approach. IEEE Trans. Image Process. 32 (2023)
Avner Shultzman, Eyar Azar, Miguel R. D. Rodrigues, Yonina C. Eldar
Generalization and Estimation Error Bounds for Model-based Neural Networks. CoRR (2023)
Zhaoyan Lyu, Gholamali Aminian, Miguel R. D. Rodrigues
On Neural Networks Fitting, Compression, and Generalization Behavior via Information-Bottleneck-like Approaches. Entropy 25 (7) (2023)
Martin Ferianc, Ondrej Bohdal, Timothy M. Hospedales, Miguel R. D. Rodrigues
Impact of Noise on Calibration and Generalisation of Neural Networks. CoRR (2023)
Gholamali Aminian, Mahed Abroshan, Mohammad Mahdi Khalili, Laura Toni, Miguel R. D. Rodrigues
An Information-theoretical Approach to Semi-supervised Learning under Covariate-shift. AISTATS (2022)
Afroditi Papadaki, Natalia Martínez, Martín Bertrán, Guillermo Sapiro, Miguel R. D. Rodrigues
Minimax Demographic Group Fairness in Federated Learning. FAccT (2022)
Wei Pu, Junjie Huang, Barak Sober, Nathan Daly, Catherine Higgitt, Ingrid Daubechies, Pier Luigi Dragotti, Miguel R. D. Rodrigues
Mixed X-Ray Image Separation for Artworks With Concealed Designs. IEEE Trans. Image Process. 31 (2022)
Yuheng Bu, Gholamali Aminian, Laura Toni, Gregory W. Wornell, Miguel R. D. Rodrigues
Characterizing and Understanding the Generalization Error of Transfer Learning with Gibbs Algorithm. AISTATS (2022)
Hongxiang Fan, Martin Ferianc, Zhiqiang Que, Xinyu Niu, Miguel R. D. Rodrigues, Wayne Luk
Accelerating Bayesian Neural Networks via Algorithmic and Hardware Optimizations. IEEE Trans. Parallel Distributed Syst. 33 (12) (2022)
Chao Zhou, Miguel R. D. Rodrigues
Blind Unmixing Using A Double Deep Image Prior. ICASSP (2022)
Gholamali Aminian, Yuheng Bu, Laura Toni, Miguel R. D. Rodrigues, Gregory W. Wornell
Information-theoretic Characterizations of Generalization Error for the Gibbs Algorithm. CoRR (2022)
Hongxiang Fan, Martin Ferianc, Zhiqiang Que, Shuanglong Liu, Xinyu Niu, Miguel R. D. Rodrigues, Wayne Luk
FPGA-Based Acceleration for Bayesian Convolutional Neural Networks. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 41 (12) (2022)
Gholamali Aminian, Yuheng Bu, Gregory W. Wornell, Miguel R. D. Rodrigues
Tighter Expected Generalization Error Bounds via Convexity of Information Measures. ISIT (2022)
Jialong Xu, Bo Ai, Wei Chen, Ang Yang, Peng Sun, Miguel R. D. Rodrigues
Wireless Image Transmission Using Deep Source Channel Coding With Attention Modules. IEEE Trans. Circuits Syst. Video Technol. 32 (4) (2022)
Wei Pu, Yonina C. Eldar, Miguel R. D. Rodrigues
Optimization Guarantees for ISTA and ADMM Based Unfolded Networks. ICASSP (2022)
Gholamali Aminian, Mahed Abroshan, Mohammad Mahdi Khalili, Laura Toni, Miguel R. D. Rodrigues
An Information-theoretical Approach to Semi-supervised Learning under Covariate-shift. CoRR (2022)
Jonathan Scarlett, Reinhard Heckel, Miguel R. D. Rodrigues, Paul Hand, Yonina C. Eldar
Theoretical Perspectives on Deep Learning Methods in Inverse Problems. IEEE J. Sel. Areas Inf. Theory 3 (3) (2022)
Jonathan Scarlett, Reinhard Heckel, Miguel R. D. Rodrigues, Paul Hand, Yonina C. Eldar
Theoretical Perspectives on Deep Learning Methods in Inverse Problems. CoRR (2022)
Gholamali Aminian, Roberto Vega, Omar Rivasplata, Laura Toni, Miguel R. D. Rodrigues
Semi-Counterfactual Risk Minimization Via Neural Networks. CoRR (2022)
Gholamali Aminian, Yuheng Bu, Gregory W. Wornell, Miguel R. D. Rodrigues
Tighter Expected Generalization Error Bounds via Convexity of Information Measures. CoRR (2022)
Gholamali Aminian, Saeed Masiha, Laura Toni, Miguel R. D. Rodrigues
Learning Algorithm Generalization Error Bounds via Auxiliary Distributions. CoRR (2022)
Chao Zhou, Miguel R. D. Rodrigues
ADMM-Based Hyperspectral Unmixing Networks for Abundance and Endmember Estimation. IEEE Trans. Geosci. Remote. Sens. 60 (2022)
Afroditi Papadaki, Natalia Martínez, Martín Bertrán, Guillermo Sapiro, Miguel R. D. Rodrigues
Minimax Demographic Group Fairness in Federated Learning. CoRR (2022)
Haiyun He, Gholamali Aminian, Yuheng Bu, Miguel R. D. Rodrigues, Vincent Y. F. Tan
How Does Pseudo-Labeling Affect the Generalization Error of the Semi-Supervised Gibbs Algorithm? CoRR (2022)
Wei Pu, Junjie Huang, Barak Sober, Nathan Daly, Catherine Higgitt, Pier Luigi Dragotti, Ingrid Daubechies, Miguel R. D. Rodrigues
A Learning Based Approach to Separate Mixed X-Ray Images Associated with Artwork with Concealed Designs. EUSIPCO (2021)
Jaweria Amjad, Zhaoyan Lyu, Miguel R. D. Rodrigues
Regression with Deep Neural Networks: Generalization Error Guarantees, Learning Algorithms, and Regularizers. EUSIPCO (2021)
Gholamali Aminian, Laura Toni, Miguel R. D. Rodrigues
Information-Theoretic Bounds on the Moments of the Generalization Error of Learning Algorithms. CoRR (2021)
Jaweria Amjad, Zhaoyan Lyu, Miguel R. D. Rodrigues
Deep Learning Model-Aware Regulatization With Applications to Inverse Problems. IEEE Trans. Signal Process. 69 (2021)
Yuheng Bu, Gholamali Aminian, Laura Toni, Miguel R. D. Rodrigues, Gregory W. Wornell
Characterizing and Understanding the Generalization Error of Transfer Learning with Gibbs Algorithm. CoRR (2021)
Afroditi Papadaki, Natalia Martínez, Martín Bertrán, Guillermo Sapiro, Miguel R. D. Rodrigues
Federating for Learning Group Fair Models. CoRR (2021)
Gholamali Aminian, Yuheng Bu, Laura Toni, Miguel R. D. Rodrigues, Gregory W. Wornell
An Exact Characterization of the Generalization Error for the Gibbs Algorithm. NeurIPS (2021)
Gholamali Aminian, Yuheng Bu, Laura Toni, Miguel R. D. Rodrigues, Gregory W. Wornell
Characterizing the Generalization Error of Gibbs Algorithm with Symmetrized KL information. CoRR (2021)
Natalia Martínez, Martín Bertrán, Afroditi Papadaki, Miguel R. D. Rodrigues, Guillermo Sapiro
Blind Pareto Fairness and Subgroup Robustness. ICML (2021)
Wei Pu, Chao Zhou, Yonina C. Eldar, Miguel R. D. Rodrigues
Robust lEarned Shrinkage-Thresholding (REST): Robust unrolling for sparse recover. CoRR (2021)
Chao Zhou, Miguel R. D. Rodrigues
An ADMM Based Network for Hyperspectral Unmixing Tasks. ICASSP (2021)
Zhaoyan Lyu, Gholamali Aminian, Miguel R. D. Rodrigues
Toward Minimal-Sufficiency in Regression Tasks: An Approach Based on a Variational Estimation Bottleneck. MLSP (2021)
Wei Pu, Chao Zhou, Yonina C. Eldar, Miguel R. D. Rodrigues
REST: Robust lEarned Shrinkage-Thresholding Network Taming Inverse Problems with Model Mismatch. ICASSP (2021)
Gholamali Aminian, Laura Toni, Miguel R. D. Rodrigues
Information-Theoretic Bounds on the Moments of the Generalization Error of Learning Algorithms. ISIT (2021)
Majid Zamani, Jure Sokolic, Dai Jiang, Francesco Renna, Miguel R. D. Rodrigues, Andreas Demosthenous
Accurate, Very Low Computational Complexity Spike Sorting Using Unsupervised Matched Subspace Learning. IEEE Trans. Biomed. Circuits Syst. 14 (2) (2020)
Pingfan Song, Lior Weizman, João F. C. Mota, Yonina C. Eldar, Miguel R. D. Rodrigues
Coupled Dictionary Learning for Multi-Contrast MRI Reconstruction. IEEE Trans. Medical Imaging 39 (3) (2020)
Zahra Sabetsarvestani, Francesco Renna, Franz J. Király, Miguel R. D. Rodrigues
Source Separation With Side Information Based on Gaussian Mixture Models With Application in Art Investigation. IEEE Trans. Signal Process. 68 (2020)
Wei Pu, Barak Sober, Nathan Daly, Catherine Higgitt, Ingrid Daubechies, Miguel R. D. Rodrigues
A Connected Auto-Encoders Based Approach for Image Separation with Side Information: With Applications to Art Investigation. ICASSP (2020)
Pingfan Song, Xin Deng, João F. C. Mota, Nikos Deligiannis, Pier Luigi Dragotti, Miguel R. D. Rodrigues
Multimodal Image Super-Resolution via Joint Sparse Representations Induced by Coupled Dictionaries. IEEE Trans. Computational Imaging 6 (2020)
Xin Deng, Pingfan Song, Miguel R. D. Rodrigues, Pier Luigi Dragotti
RADAR: Robust Algorithm for Depth Image Super Resolution Based on FRI Theory and Multimodal Dictionary Learning. IEEE Trans. Circuits Syst. Video Technol. 30 (8) (2020)
Wei Pu, Barak Sober, Nathan Daly, Zahra Sabetsarvestani, Catherine Higgitt, Ingrid Daubechies, Miguel R. D. Rodrigues
Image Separation with Side Information: A Connected Auto-Encoders Based Approach. CoRR (2020)
Gholamali Aminian, Laura Toni, Miguel R. D. Rodrigues
Jensen-Shannon Information Based Characterization of the Generalization Error of Learning Algorithms. CoRR (2020)
Jaweria Amjad, Zhaoyan Lyu, Miguel R. D. Rodrigues
Model-Aware Regularization For Learning Approaches To Inverse Problems. CoRR (2020)
Gholamali Aminian, Laura Toni, Miguel R. D. Rodrigues
Jensen-Shannon Information Based Characterization of the Generalization Error of Learning Algorithms. ITW (2020)
Daniel Jakubovitz, Miguel R. D. Rodrigues, Raja Giryes
Lautum Regularization for Semi-Supervised Transfer Learning. ICCV Workshops (2019)
Martín Bertrán, Natalia Martínez, Afroditi Papadaki, Qiang Qiu, Miguel R. D. Rodrigues, Galen Reeves, Guillermo Sapiro
Adversarially Learned Representations for Information Obfuscation and Inference. ICML (2019)
Nir Shlezinger, Yonina C. Eldar, Miguel R. D. Rodrigues
Hardware-Limited Task-Based Quantization. SPAWC (2019)
Nir Shlezinger, Yonina C. Eldar, Miguel R. D. Rodrigues
Asymptotic Task-Based Quantization With Application to Massive MIMO. IEEE Trans. Signal Process. 67 (15) (2019)
Nir Shlezinger, Yonina C. Eldar, Miguel R. D. Rodrigues
Hardware-Limited Task-Based Quantization. IEEE Trans. Signal Process. 67 (20) (2019)
Pingfan Song, Yonina C. Eldar, Gal Mazor, Miguel R. D. Rodrigues
Magnetic Resonance Fingerprinting Using a Residual Convolutional Neural Network. ICASSP (2019)
Jaweria Amjad, Zhaoyan Lyu, Miguel R. D. Rodrigues
Deep Learning for Inverse Problems: Bounds and Regularizers. CoRR (2019)
Nir Shlezinger, Yonina C. Eldar, Miguel R. D. Rodrigues
Task-Based Quantization for Massive MIMO Channel Estimation. ICASSP (2019)
Pingfan Song, Yonina C. Eldar, Gal Mazor, Miguel R. D. Rodrigues
HYDRA: Hybrid Deep Magnetic Resonance Fingerprinting. CoRR (2019)
Daniel Jakubovitz, Miguel R. D. Rodrigues, Raja Giryes
Lautum Regularization for Semi-supervised Transfer Learning. CoRR (2019)
Pingfan Song, Lior Weizman, João F. C. Mota, Yonina C. Eldar, Miguel R. D. Rodrigues
Coupled Dictionary Learning for Multi-contrast MRI Reconstruction. CoRR (2018)
Pingfan Song, Miguel R. D. Rodrigues
Multimodal Image Denoising based on Coupled Dictionary Learning. CoRR (2018)
Nir Shlezinger, Yonina C. Eldar, Miguel R. D. Rodrigues
Hardware-Limited Task-Based Quantization. CoRR (2018)
Zahra Sabetsarvestani, Franz J. Király, Miguel R. D. Rodrigues
Entry-wise Matrix Completion from Noisy Entries. EUSIPCO (2018)
Pingfan Song, Miguel R. D. Rodrigues
Multi-Modal Image Processing Based on Coupled Dictionary Learning. SPAWC (2018)
Miguel R. D. Rodrigues, Helmut Bölcskei, Stark C. Draper, Yonina C. Eldar, Vincent Yan Fu Tan
Introduction to the Issue on Information-Theoretic Methods in Data Acquisition, Analysis, and Processing. IEEE J. Sel. Top. Signal Process. 12 (5) (2018)
Pingfan Song, Miguel R. D. Rodrigues
Multimodal Image Denoising Based on Coupled Dictionary Learning. ICIP (2018)
Pingfan Song, Miguel R. D. Rodrigues
Multi-modal Image Processing based on Coupled Dictionary Learning. CoRR (2018)
Martín Bertrán, Natalia Martínez, Afroditi Papadaki, Qiang Qiu, Miguel R. D. Rodrigues, Guillermo Sapiro
Learning to Collaborate for User-Controlled Privacy. CoRR (2018)
Evangelos Zimos, João F. C. Mota, Evaggelia Tsiligianni, Miguel R. D. Rodrigues, Nikos Deligiannis
Data aggregation and recovery for the Internet of Things: A compressive demixing approach. WCNC (2018)
Pingfan Song, Lior Weizman, João F. C. Mota, Yonina C. Eldar, Miguel R. D. Rodrigues
Coupled Dictionary Learning for Multi-Contrast MRI Reconstruction. ICIP (2018)
Meng-Yang Chen, Francesco Renna, Miguel R. D. Rodrigues
Compressive Sensing With Side Information: How to Optimally Capture This Extra Information for GMM Signals? IEEE Trans. Signal Process. 66 (9) (2018)
Jaweria Amjad, Jure Sokolic, Miguel R. D. Rodrigues
On Deep Learning for Inverse Problems. EUSIPCO (2018)
Zahra Sabetsarvestani, Francesco Renna, Franz J. Király, Miguel R. D. Rodrigues
Source Separation in the Presence of Side Information: Necessary and Sufficient Conditions for Reliable De-Mixing. GlobalSIP (2018)
Daniel Jakubovitz, Raja Giryes, Miguel R. D. Rodrigues
Generalization Error in Deep Learning. CoRR (2018)
Jure Sokolic, Raja Giryes, Guillermo Sapiro, Miguel R. D. Rodrigues
Robust Large Margin Deep Neural Networks. IEEE Trans. Signal Process. 65 (16) (2017)
Miguel R. D. Rodrigues, Nikos Deligiannis, Lifeng Lai, Yonina C. Eldar
Rate-distortion trade-offs in acquisition of signal parameters. ICASSP (2017)
Nikos Deligiannis, João F. C. Mota, Evangelos Zimos, Miguel R. D. Rodrigues
Heterogeneous Networked Data Recovery From Compressive Measurements Using a Copula Prior. IEEE Trans. Commun. 65 (12) (2017)
Jure Sokolic, Miguel R. D. Rodrigues, Qiang Qiu, Guillermo Sapiro
Learning to Identify While Failing to Discriminate. ICCV Workshops (2017)
Nikos Deligiannis, João F. C. Mota, Bruno Cornelis, Miguel R. D. Rodrigues, Ingrid Daubechies
Multi-Modal Dictionary Learning for Image Separation With Application in Art Investigation. IEEE Trans. Image Process. 26 (2) (2017)
Jure Sokolic, Qiang Qiu, Miguel R. D. Rodrigues, Guillermo Sapiro
Learning to Succeed while Teaching to Fail: Privacy in Closed Machine Learning Systems. CoRR (2017)
Jure Sokolic, Raja Giryes, Guillermo Sapiro, Miguel R. D. Rodrigues
Generalization Error of Invariant Classifiers. AISTATS (2017)
Liming Wang, Minhua Chen, Miguel R. D. Rodrigues, David Wilcox, A. Robert Calderbank, Lawrence Carin
Information-Theoretic Compressive Measurement Design. IEEE Trans. Pattern Anal. Mach. Intell. 39 (6) (2017)
João F. C. Mota, Nikos Deligiannis, Miguel R. D. Rodrigues
Compressed Sensing With Prior Information: Strategies, Geometry, and Bounds. IEEE Trans. Inf. Theory 63 (7) (2017)
Pingfan Song, Xin Deng, João F. C. Mota, Nikos Deligiannis, Pier Luigi Dragotti, Miguel R. D. Rodrigues
Multimodal Image Super-Resolution via Joint Sparse Representations induced by Coupled Dictionaries. CoRR (2017)
Hugo Reboredo, Francesco Renna, A. Robert Calderbank, Miguel R. D. Rodrigues
Bounds on the Number of Measurements for Reliable Compressive Classification. IEEE Trans. Signal Process. 64 (22) (2016)
Jure Sokolic, Raja Giryes, Guillermo Sapiro, Miguel R. D. Rodrigues
Generalization Error of Invariant Classifiers. CoRR (2016)
Liming Wang, Francesco Renna, Xin Yuan, Miguel R. D. Rodrigues, A. Robert Calderbank, Lawrence Carin
A general framework for reconstruction and classification from compressive measurements with side information. ICASSP (2016)

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Publication Activity (10 Years)

Top Topics

Top Venues

Miguel R. D. Rodrigues