2023 - Research.com Computer Science in Portugal Leader Award
2022 - Research.com Computer Science in Portugal Leader Award
2010 - IEEE Fellow For contributions to pattern recognition and computer vision
2008 - Fellow of the International Association for Pattern Recognition (IAPR) For contributions to unsupervised and supervised learning, image analysis, and wavelet-based image restoration.
His research investigates the link between Inverse problem and topics such as Mathematical analysis that cross with problems in Separable space and Monotonic function. His Separable space study frequently links to related topics such as Mathematical analysis. He integrates Monotonic function and Convex function in his research. Many of his studies involve connections with topics such as Pattern recognition (psychology) and Artificial intelligence. His research combines Artificial intelligence and Pattern recognition (psychology). In his study, he carries out multidisciplinary Mathematical optimization and Quadratic programming research. He connects Quadratic programming with Basis pursuit in his research. He integrates Basis pursuit with Matching pursuit in his research. He merges Matching pursuit with Wavelet in his research.
His Smoothness research focuses on Mathematical analysis and how it connects with Inverse problem. His study brings together the fields of Mathematical analysis and Inverse problem. His work in Regular polygon covers topics such as Geometry which are related to areas like Quadratic equation. In his work, he performs multidisciplinary research in Quadratic equation and Geometry. Artificial intelligence is closely attributed to Regularization (linguistics) in his research. His Minimum description length research extends to Algorithm, which is thematically connected. Mário A. T. Figueiredo combines Minimum description length and Statistics in his research. Statistics and Random field are frequently intertwined in his study. He incorporates Mathematical optimization and Iterative method in his research.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Gradient Projection for Sparse Reconstruction: Application to Compressed Sensing and Other Inverse Problems
M.A.T. Figueiredo;R.D. Nowak;S.J. Wright.
IEEE Journal of Selected Topics in Signal Processing (2007)
Unsupervised learning of finite mixture models
M.A.T. Figueiredo;A.K. Jain.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2002)
Sparse Reconstruction by Separable Approximation
S.J. Wright;R.D. Nowak;M.A.T. Figueiredo.
IEEE Transactions on Signal Processing (2009)
A New TwIST: Two-Step Iterative Shrinkage/Thresholding Algorithms for Image Restoration
J.M. Bioucas-Dias;M.A.T. Figueiredo.
IEEE Transactions on Image Processing (2007)
An EM algorithm for wavelet-based image restoration
M.A.T. Figueiredo;R.D. Nowak.
IEEE Transactions on Image Processing (2003)
Fast Image Recovery Using Variable Splitting and Constrained Optimization
Manya V Afonso;José M Bioucas-Dias;Mário A T Figueiredo.
IEEE Transactions on Image Processing (2010)
Image classification for content-based indexing
A. Vailaya;M.A.T. Figueiredo;A.K. Jain;Hong-Jiang Zhang.
IEEE Transactions on Image Processing (2001)
An Augmented Lagrangian Approach to the Constrained Optimization Formulation of Imaging Inverse Problems
M V Afonso;José M Bioucas-Dias;Mário A T Figueiredo.
IEEE Transactions on Image Processing (2011)
Sparse multinomial logistic regression: fast algorithms and generalization bounds
B. Krishnapuram;L. Carin;M.A.T. Figueiredo;A.J. Hartemink.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2005)
On the Role of Sparse and Redundant Representations in Image Processing
Michael Elad;Mario A T Figueiredo;Yi Ma.
Proceedings of the IEEE (2010)
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