Self-Supervised Representation Learning: Introduction, advances, and challenges
Self-supervised representation learning (SSRL) methods aim to provide powerful, deep feature learning without the requirement of large annotated data…
Read moreMay 2022
<p>Volume 39 | Issue 3</p>
Federated Learning: A signal processing perspective
The dramatic success of deep learning is largely due to the availability of data. Data samples are often acquired on edge devices, such as…
Read moreFire, Water, and Signal Processing: Researchers are turning to signal processing to help them address challenges posed by two of the planet’s fundamental forces
Fire and water, two of nature’s basic forces, are each capable of sustaining or destroying life and property. Research projects in California and…
Read moreEthical Dilemmas in the Sciences
“Science without conscience is only ruin of the soul” said François Rabelais. This centuries-old quote still resonates, today maybe louder than ever…
Read moreOn Dual-Use Information Technology
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…
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