In past decades, conventional communication primarily focused on how to accurately and effectively transmit symbols, which is categorized as the first level of communications by Shannon and Weaver. With the developments of cellular communication systems, the achieved transmission rate is gradually approaching to the Shannon limit. 

The Principal Component Analysis (PCA) is considered to be a quintessential data preprocessing tool in many machine learning applications. But the high dimensionality and massive scale of data in several of these applications means the traditional centralized PCA solutions are fast becoming irrelevant for them. 

The Signal Processing Society (SPS) has 12 Technical Committees that support a broad selection of signal processing-related activities defined by the scope of the Society.

For our 50th anniversary in 1998, the IEEE Signal Processing Society (SPS) worked with the IEEE History Center to prepare a monograph outlining the history of the Society. In 2023, we will celebrate the 75th anniversary of the IEEE Signal Processing Society!

As the standardization of 5G gradually solidifies, researchers are speculating what 6G will be. One common theme is that radio sensing functionality would be integrated into 6G networks in a low-cost and fast manner. 

The IEEE Signal Processing Society invites nominations for the SPS Challenges and Data Collections Chair position. The term for the position is two years (1 January 2023-31 December 2024).  Nominations must be received no later than 15 June 2022.

Privacy issues and communication costs are both major concerns in distributed optimization in networks. There is often a tradeoff between them because encryption methods used for privacy-preservation often introduce significant communication overhead.

The Steering Committee of IEEE Transactions on Wireless Communications (TWC) invites nominations for the position of Editor-in-Chief for the journal for a two-year term starting on 1 January 2023. The term is renewable for up to additional two years.

Dr. Meredith Ringel Morris is Director of People + AI Research at Google. Prior to joining Google Research, Dr. Morris was Research Area Manager for Interaction, Accessibility, and Mixed Reality at Microsoft Research, where she founded Microsoft’s Ability research group. 

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.