Special Sessions
In addition to contributed sessions, the workshop will also have a total of 18 special sessions. These special sessions cover a wide-range of topics of emerging interest and are being organized by some of the leading researchers in the signal processing community:
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Beyond Massive MIMO – New Concepts and Signal Processing
Emil Björnson and Luca Sanguinetti
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Mathematical Foundations of Deep Learning
René Vidal and Jeremias Sulam
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Distributed learning and optimization over networks
Ali H. Sayed and Roula Nassif
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Principles of Dynamics and Control in Machine Learning
Mark A. Davenport, Jarvis Haupt, Christopher J. Rozell, Michael B. Wakin
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IoT signal processing for radar applications
Kumar Vijay Mishra, Bhavani Shankar, Björn Ottersten
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Learning Over Graphs
Sundeep Prabhakar Chepuri, Santiago Segarra, Mario Coutino
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Signal Processing and Machine Learning Methods for Acoustic Sensor Networks
Walter Kellermann and Sharon Gannot
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Machine learning and applications to radar and array processing
Maria Sabrina Greco and Frederic Pascal
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The Intersection of Optimization Theory and Information Processing
Esa Ollila, Visa Koivunen, Abdelhak M. Zoubir
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Robust Statistics for Signal Processing
Esa Ollila, Visa Koivunen, Abdelhak M. Zoubir
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Structured Matrix and Tensor Methods
Xiao Fu, Nicolas Gillis, Kejun Huang
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Scale-free and nonlinear multivariate signal and image analysis
Patrice Abry, Herwig Wendt
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Statistical physics for signal processing and learning
Jean Barbier
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Large Random Matrix Theory in Signal Processing and Machine Learning
Xavier Mestre, Pascal Vallet
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Structured sparsity for compressed sensing problems
Marius Pesavento and Martin Haardt
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Current trends in computational spectral sensing and imaging
Jean-Philippe Ovarlez, Henry Arguello
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Computational biomedical imaging
Adrian Basarab and Denis Kouamé
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Inference in high-dimensional spaces by Monte Carlo methods
Petar Djuric, Victor Elvira