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[2018-07-10] Dr. Sun-Yuan Kung, Princeton University,” On A Novel Machine Learning Paradigm: MIND-Net”

非專題討論演講公告
張貼人:宋欣薏公告日期:2018-06-27
Title: On A Novel Machine Learning Paradigm: MIND-Net
Date: 2018-07-10 13:00-16:30
Location: R201, Barry Lam Hall
Speaker: Dr. Sun-Yuan Kung, Princeton University

 

Abstract:

美國普林斯頓大學的深度學習/機器學習/人工智慧專家 貢三元教授,將在此次演講揭開深度學習的黑箱,
深入淺出的說明深度學習的原理與運作的原理,並提出新興的機器學習模式:MIND-Net此模式善用判別信息(Discriminant InformationDI),以增加分類網路中某變數的判別能力、達到較高的分辨性。在數學上,DI相當於GaussLSEFisherFDRShannon的相互信息等,我們將解釋為什麼較高的DI意味著較高的線性可分性以及較高的辨別性;同時,在結構方面,MIND-Net也提供了另一種具有成本效益的解決方案,我們可以透過橫向擴充具有附加隨機化節點的繼承層並應用反向傳播BP)學習,提高與增強網路的判別力。MIND-Net能被應用於模擬和真實的數據集,並能有效的改善和提昇深度學習的分析和結構問題。


Biography:

Sun-Yuan Kung was born in Taiwan on January 2, 1950. He received the B.S. in Electrical Engineering from the National Taiwan University in 1971; M.S. in Electrical Engineering from the University of Rochester in 1974; and Ph.D. in Electrical Engineering from Stanford University in 1977. From 1977 to 1987, he was on the faculty of Electrical Engineering-Systems at the University of Southern California. In 1984, he was a Visiting Professor at Stanford University and later in the same year, a visiting professor at the Delft University of Technology. Since September 1987, he has been a Professor in the Department of Electrical Engineering, Princeton University. He currently serves on the IEEE Technical Committees on VLSI Signal Processing and Neural Networks and an Editor-in-Chief of Journal of VLSI Signal Processing.Membership in Societies: IEEE (Fellow), ACM (Member).

最後修改時間:2018-07-10 AM 10:00

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