Institute of Global Innovation Research
|Date||2019.7.5 (19 : 25 - 21：05)|
|Venue||LINE Corporaton ( JR SHINJUKU MIRAINA TOWER, 4-1-6 Shinjuku, Shinjuku-ku, Tokyo)|
|Speaker / Topic||19:35～20:30 (Language: English)
Dr. Antonio Ortega (Professor, University of Southern California, U.S.A.)
"Making sense of data on networks: a graph signal processing approach"
As technology for sensing, computing and communicating continues to improve, we all are becoming increasingly reliant on a series of very large scale networks: the Internet, which connects computers and phones, as well as a rapidly growing number of devices and systems (the Internet of Things); large information networks such as the web or online social networks; even networks that have existed for decades (e.g., transportation or electrical networks) are now more complex and increasingly a focus of data-driven optimization. This trend is one of the key motivations for research in the emerging field of graph signal processing (GSP). GSP seeks to develop new methods to analyze graph signals, i.e., data associated to nodes in a network, using tools similar to those applied for processing of conventional signals, such as audio, speech or images. In this talk we provide an introduction to graph signal processing (GSP). We review notions of frequency can be applied to graph signals, then describe how these are used to develop filtering and sampling strategies. We then discuss recent advances in the development of GSP tools and illustrate them with applications in sensing, imaging and machine learning.
Antonio Ortega received his undergraduate and doctoral degrees from the Universidad Politecnica de Madrid, Madrid, Spain and Columbia University, New York, NY, respectively. In 1994 he joined the Electrical Engineering department at the University of Southern California (USC), where he is currently a Professor and has served as Associate Chair. He is a Fellow of the IEEE and EURASIP, and a member of ACM and APSIPA. He is currently a member of the Board of Governors of the IEEE Signal Processing Society and the Editir-in-Chief of the IEEE Transactions on Signal and Information Processing over Networks.
He has received several paper awards, including the 2016 Signal Processing Magazine award. His recent research work is focusing on graph signal processing, machine learning, multimedia compression and wireless sensor networks.
20:40～21:05 (Language: Japanese)
戸上 真人（LINE株式会社 Research Labs、博士(工学)）
"Multi-channel speech source separation with deep learning"
2016/9まで日立製作所中央研究所の音声音響信号処理ユニットのユニットリーダー主任研究員として、対話ロボット、テレビ会議システム向けの音響信号処理の研究開発・チームリーディング。その後、2018/5までシリコンバレーの日立アメリカの ラボに所属しStanford大学Stanford Data Science InitiativeのVisiting Scholar。2018/6よりLINE Research Labs/Senior Researcher。15年以上に渡り音声・音響信号処理の研究開発に従事。IEEE Senior Member。
|Intended for||Researcher/Developer/Student who is interested in AI related technology|
|Co-Organized by||Institute of Global Innovation “Life Science” Tanaka Team
Excellent Leader Development for Super Smart Society by New Industry Creation and Diversity
|Contact||Institute of Global Innovation Research, Institute of Engineering,
Assoc. Prof. Yuichi Tanaka
Email: ytnk (at) cc.tuat.ac.jp
|Remarks||For registration, please visit:
LINE AI Talk #02 (https://line.connpass.com/event/135072/)
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