February Fourier Talks 2015

Petros Boufounos

Mitsubishi Electric Research Labs (MERL)


Coding for inference: Universal Quantization and Embeddings


Inference over a transmission channel is increasingly becoming an important problem in a variety of applications. In such applications, low latency and bit-rate consumption are often critical performance metrics, making data compression necessary. In this talk I will describe how universal quantization and universal embeddings provide a general approach to compression for a number of problems of signal processing over a channel. These include inference based on nearest-neighbors and Support Vector Machines (SVMs), clustering, as well as conventional compression and distributed compression. I will demonstrate the significant gains from universal compression both in coding performance as well as in design flexibility. In addition, I will explore the very interesting connection of universal embeddings with kernel methods and machine learning.


Petros T. Boufounos is a Principal Member of Research Staff at Mitsubishi Electric Research Laboratories (MERL) and a visiting scholar at the Rice University Electrical and Computer Engineering department. Dr. Boufounos completed his undergraduate and graduate studies at MIT. He received the S.B. degree in Economics in 2000, the S.B. and M.Eng. degrees in Electrical Engineering and Computer Science (EECS) in 2002, and the Sc.D. degree in EECS in 2006. Between September 2006 and December 2008, he was a postdoctoral associate with the Digital Signal Processing Group at Rice University. Dr. Boufounos joined MERL in January 2009. Dr. Boufounos' immediate research focus includes signal acquisition and processing, frame theory, quantization and data representations. He is also interested into how signal acquisition interacts with other fields that use sensing extensively, such as machine learning, robotics and mechatronics. Dr. Boufounos is a Senior Area Editor at IEEE Signal Processing Letters. He has received the Ernst A. Guillemin Master Thesis Award for his work on DNA sequencing, the Harold E. Hazen Award for Teaching Excellence, both from the MIT EECS department, and has been an MIT Presidential Fellow. He is also a senior member of the IEEE and a member of Sigma Xi, Eta Kappa Nu, and Phi Beta Kappa.

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