As the modern, fast-paced machine learning theory tends to rely on a broad range of mathematical tools, there is a need for a communication nexus supporting leading, collaborative theoretical machine learning research of SNU's theory-oriented members. To this end, the SNU Theoretical AI research Group (STAG) supports regular and intimate interaction among its members who bring a broad theoretical background and coordinates with the graduate school of artificial intelligence. The key goals of STAG include probing new theoretical AI research directions, pursuing synergistic collaborative research, and teaching and advising students of the graduate school of artificial intelligence. We expect the activities of STAG to strengthen the theoretical machine learning research of SNU.
머신러닝은 다양한 수학적 도구를 활용하는 기술입니다. AI이론연구그룹(STAG)에서는 수학자들이 중심이 되어 인공지능 전문가들과 긴밀하게 교류하며 수학을 바탕으로 머신러닝을 연구합니다.
Bayesian statistics (이재용), Stochastic process (서인석, 박형빈), Topological data analysis(국웅, Otto van Koert), Deep Learning (송현오), Natural language processing(정교민), Reinforcement learning and control(심형보, 양인순), Quantum information theory (이훈희), Optimization (류경석, 이재욱), Security and privacy (천정희, 현동훈)
천정희, 류경석 교수(수리과학부)가
이론 AI 연구센터에 대해 영상으로 설명합니다.
천정희(센터장) · 국웅 · 류경석 · 박형빈 · 서인석 · 송현오 · 심형보 · 양인순 · 이재용 · 이재욱 · 이훈희 · 정교민 · 현동훈 · Otto van Koert