Time+Place: | Tuesday 05/04/2016 14:30 Room 337-8 Taub Bld. |

Title: | Designing Communication Receivers Using Machine Learning Techniques |

Speaker: | Brian M. Kurkoski - COLLOQUIUM LECTURE http://www.jaist.ac.jp/is/labs/bits/brian |

Affiliation: | Japan Advanced Institute of Science and Technology (JAIST), Nomi, Japan |

Host: | Eitan Yaakobi |

Any communication receiver, for all its complexity, can be decomposed into a sequence of operations on an input received value sequence to obtain an output estimated transmitted sequence. Such receivers are widely used in modern forms of wireless communications and data storage. Practical implementations are in VLSI, where continuous or floating-point values are quantized to a fixed number of bits. The objective is to directly design fixed-precision operations to maximize mutual information. For the design of communication systems, maximization of mutual information gives the highest possible communications rate, and thus is a natural choice as a design criteria. Each operation in a sequence of decoding operations can be implemented using a lookup table, and the core idea is to design lookup tables that maximize mutual information. We call this the "max-LUT method." To do this, we leverage some well-known results from machine learning theory. In particular, the design of classifiers that minimize conditional entropy is equivalent to the design of quantizers that maximize mutual information. To avoid exponential complexity, a variation of the K-means clustering algorithm, called KL-means algorithm, is used to find the quantizer (classifier). There is a natural connection between a quantizer and a lookup table. These ideas are applied to the implementation of fixed-precision algorithms for decoding error-correcting codes, particularly low-density parity check codes. Short Bio: Brian M. Kurkoski is an Associate Professor at the Japan Advanced Institute of Science and Technology (JAIST) in Nomi, Japan. Born in Portland, Oregon, he received the B.S. degree from the California Institute of Technology in 1993, and then worked at two California startups. He received the M.S. and Ph.D. degrees from the University of California San Diego in 2000 and 2004, respectively. He received a JSPS Postdoctoral Fellowship from 2004 to 2006, while at the University of Electro-Communications in Tokyo, Japan, where he continued as Associate Professor from 2007 to 2012. He has been at JAIST since 2012. He was an associate editor for IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences from 2010 to 2014. He is currently the secretary of the Data Storage Technical Committee, a technical committee of the IEEE Communications Society. He has organized or been technical co-chair for various conference tracks and workshops on coding for data storage. His research interests include coding theory, information theory and communication theory and their applications. Refreshments will be served from 14:15 Lecture starts at 14:30