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The Latest News, Articles, and Events in Signal Processing

IEEE Signal Processing Magazine
Self-supervised representation learning (SSRL) methods aim to provide powerful, deep feature learning without the requirement of large annotated data sets, thus alleviating the annotation bottleneck-one of the main barriers to the practical deployment of deep learning today. These techniques have advanced rapidly in recent years, with their efficacy approaching and sometimes surpassing fully supervised pretraining alternatives across a variety of data modalities, including image, video, sound, text, and graphs.
IEEE Signal Processing Magazine
The dramatic success of deep learning is largely due to the availability of data. Data samples are often acquired on edge devices, such as smartphones, vehicles, and sensors, and in some cases cannot be shared due to privacy considerations. Federated learning is an emerging machine learning paradigm for training models across multiple edge devices holding local data sets, without explicitly exchanging the data. Learning in a federated manner differs from conventional centralized machine learning and poses several core unique challenges and requirements, which are closely related to classical problems studied in the areas of signal processing and communications.
IEEE Signal Processing Magazine
Fire and water, two of nature’s basic forces, are each capable of sustaining or destroying life and property. Research projects in California and Hawaii are, respectively, helping displaced families cope with devasting wildfires, and investigating a way to increase water supply availability on isolated islands. Both projects are relying on signal processing to help them meet their goals.
IEEE Signal Processing Magazine
“Science without conscience is only ruin of the soul” said François Rabelais. This centuries-old quote still resonates, today maybe louder than ever. I began to write this editorial at the end of February when Russian tanks and soldiers invaded Ukraine and waves of bombers began dropping their bombs on Ukrainian cities, targeting civilian buildings, hospitals, and schools. This dramatic event was a shock to Europeans, since most of them have lived in relative peace for more than 70 years.
IEEE Signal Processing Magazine
While I am writing this column, the Russia–Ukraine war is raging. As bombings, destruction, and human suffering flood the daily news, I deeply feel the pain of our Ukrainian colleagues, those who have friends and family in the affected areas, those who had to put their studies and careers on hold to fight for their survival. I also acknowledge the agony of those around the world who are watching the developments in horror, trying to comprehend why such insanity was necessary.

Substantial progress has been made recently on developing provably accurate and efficient algorithms for low-rank matrix factorization via nonconvex optimization. While conventional wisdom often takes a dim view of nonconvex optimization algorithms due to their susceptibility to spurious local minima, simple iterative methods such as gradient descent have been remarkably successful in practice. 

Date: June 18, 2020
Time: 8:30 PM ET (New York Time)
Title: A Policy-Based Security Architecture for Software-Defined Networks

Date: July 15, 2020
Time: 1:00 PM ET (New York Time)
Title: 20 Years of Musical Genre Classification of Audio Signals
Registration | Full webinar details

Date: August 21, 2020
Time: 8:00 AM ET (New York Time)
Title: An Algorithmic Investigation of Hybrid Beamforming for 5G and Beyond Networks
Registration | Full webinar details

Date: September 21, 2020
Time: 11:00 AM ET (New York Time)
Title: How the Mobile Phone Became a Camera
Registration | Full webinar details

Telecom Paris, Institut polytechnique de Paris

We have multiple openings for PhD studentsPostdoctoral Researchers and R&D Engineers at Télécom Paris, Institut polytechnique de Paris, in the “Signal, Statistics and Learning (S2A) team. 

All positions are located at Telecom Paris, 19 place Marguerite Perey, 91120 Palaiseau, France.

Start of the positions: October/November 2022 (for PhDs/Engineer), January 2023 for PostDoc

Subject:

Date: December 9, 2021
Time: 11:00 AM ET (New York Time)
Title: Scaling and Scalability: Accelerating Ill-conditioned Low-rank Estimation via Scaled Gradient Descent
Registration | Full webinar details

Date: December 10, 2021
Time: 10:00 AM ET (New York Time)
Title: Image Fusion with Convolutional Sparse Representation
Registration | Full webinar details

Date: December 20, 2021
Time: 8:00 AM ET (New York Time)
Title: Infinite-Dimensional Expansion for Sound Field Estimation with Application to Spatial Audio
Registration | Full webinar details

Date: December 8, 2021
Time: 08:20 AM ET (New York Time)
Title: Is Machine Learning Security IFS-Business as Usual?
Registration | Full webinar details

Date: January 26, 2022
Time: 9:00 AM ET (New York Time)
Title: Bayesian Multi-object Tracking: Probability Hypothesis Density Filter and Beyond
Registration | Full webinar details

Date: February 24, 2022
Time: 11:00 AM ET (New York Time)
Title: Recent Advances of Deep Learning within X-ray Security Imaging
Registration | Full webinar details

Date: January 27, 2022
Time: 10:00 AM ET (New York Time)
Title: Signal Processing for THz Communications
Registration | Full webinar details

Date: February 17, 2022
Time: 3:00 PM (Paris Time)
Title: Revisiting MIMO from a Circuits Perspective
Registration | Full webinar details

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