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[세미나] [전기전자세미나] 10월 19일 Deep metric learning for retrieval and clustering

2017-10-13l Hit 162


824. Deep metric learning

for retrieval and clustering

 

 

¾연사: 송현오 (서울대학교 컴퓨터공학부 조교수)

¾일시: 201710 19() 오후 5:00~6:00

¾장소: 서울대학교 제1공학관(301) 118

 

 

Abstract:

Learning to measure the similarity among arbitrary groups of data is of great practical importance, and is used in a variety of tasks such as feature based retrieval, clustering, near duplicate detection, verification, feature matching, domain adaptation, weakly supervised learning, etc. In this talk, we'll explore the state of the art in deep metric learning with applications in retrieval, clustering, and unsupervised domain adaptation.

 

 

Biography:

  • 학력

    2014   Ph.D. in Computer Science, UC Berkeley

    2013   M.S. in Computer Science, UC Berkeley

    2008   M.S. in Mechanical Engineering, Stanford University

    2006   B.S. in Mechanical Engineering, Hanyang University

  • 주요경력

    2017.09. – now: Dept. of Computer Science and Engineering, SNU (Assistant Professor)

    2016.07. – 2017.08.: Google Research (Research Scientist)

    2014.11. – 2016.07.: Stanford University (Postdoctoral fellow)

    2013: INRIA Grenoble (Visiting researcher)

    2013: IBM Research (Research intern)

  • Academic website

    http://cs.stanford.edu/~hsong

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