BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//CERN//INDICO//EN
BEGIN:VEVENT
SUMMARY:데이터의 프라이버시를 보존하는 기계학습 (Safe Ma
 chine Learning toward Private AI)
DTSTART;VALUE=DATE-TIME:20191108T010000Z
DTEND;VALUE=DATE-TIME:20191108T012000Z
DTSTAMP;VALUE=DATE-TIME:20260723T092042Z
UID:indico-contribution-6-32@sshep.snu.ac.kr
DESCRIPTION:Speakers: Jung Hee Cheon (Seoul National University)\n기계
 학습(Machine Learning)은 데이터로부터 이를 도출한 함수를 
 유추하는 과정으로 최근 다양한 분야에서 흥미로운 응
 용들이 제시되고 있다. 기계학습이 좋은 성과를 거두려
 면 데이터의 확보가 필수적인데 개인 프라이버시 문제 
 혹은 데이터 주권의 문제로 인해 좋은 데이터를 확보하
 는 것이 쉽지 않은 일이다. 동형암호는 암호화한 데이터
 상에서 복호화없이 기계학습의 훈련단계(Training)나 예측
 단계(Inference)를 수행할 수 있도록 하며\, 이를 통해 데이
 터의 프라이버시 문제를 극복하고 Private AI의 시대를 열
 어가고 있다. 본 강연에서는 이 분야의 최근 결과들로 
 동형 회귀분석(Homomorphic Logistric Regression)\, 동형 심층신
 경망(Homomorphic Deep Neural Network)\, 동형 의사결정나무(Homomo
 rphic Decision Tree)등의 결과와 이의 신용정보\, 의료\, 마케
 팅 등에의 응용을 소개하도록 한다.\n\nhttps://sshep.snu.ac.kr
 /event/107/contributions/32/
LOCATION:Seoul National University\, College of Natural Sciences\, Buildin
 g 25-1 국제회의실 (International Conference Hall)
URL:https://sshep.snu.ac.kr/event/107/contributions/32/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Harmonic Data Analysis for Shape and Centrality
DTSTART;VALUE=DATE-TIME:20191108T014000Z
DTEND;VALUE=DATE-TIME:20191108T020000Z
DTSTAMP;VALUE=DATE-TIME:20260723T092042Z
UID:indico-contribution-6-38@sshep.snu.ac.kr
DESCRIPTION:Speakers: Woong Kook (Seoul National University)\nHarmonic dat
 a analysis aims to provide topological and combinatorial summaries of data
  sets by representing them as simplicial complexes. Topological data analy
 sis\, which we shall review briefly\, initiated a topological approach and
  introduced shape of data as a new data scientific feature. Recently\, the
  need for simplicial complexes for data analysis arose again due to the em
 ergence of simplicial networks for modeling higher order relations among d
 ata points\, which requires both topological insight and combinatorial pre
 cision. In this talk\, we will present methods from topological combinator
 ics for refining data shape via harmonic cycles and computing network cent
 rality via simplicial effective conductance. Applications to medicine and 
 social networks will be presented. We will also describe recent experiment
 s in machine learning incorporating mathematical data summary.\n\nhttps://
 sshep.snu.ac.kr/event/107/contributions/38/
LOCATION:Seoul National University\, College of Natural Sciences\, Buildin
 g 25-1 국제회의실 (International Conference Hall)
URL:https://sshep.snu.ac.kr/event/107/contributions/38/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Quantum AI\, Quantum Machine Learning
DTSTART;VALUE=DATE-TIME:20191108T012000Z
DTEND;VALUE=DATE-TIME:20191108T014000Z
DTSTAMP;VALUE=DATE-TIME:20260723T092042Z
UID:indico-contribution-6-39@sshep.snu.ac.kr
DESCRIPTION:Speakers: Dongpyo Chi (Seoul National University)\nRecent deve
 lopment in quantum technology together with advances in quantum algorithms
  impacts the field of quantum AI and machine learning. Many quantum machin
 e learning algorithms and their applications to AI are being appeared. We 
 present some of these and also our work in the field.\n\nhttps://sshep.snu
 .ac.kr/event/107/contributions/39/
LOCATION:Seoul National University\, College of Natural Sciences\, Buildin
 g 25-1 국제회의실 (International Conference Hall)
URL:https://sshep.snu.ac.kr/event/107/contributions/39/
END:VEVENT
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