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강연자 정교민
소속 서울대 전기공학부
date 2014-10-16
이 강연에서는 최근 음악, 영화 추천 등 다양한 Recommendation System의 기본 아이디어인 Matrix Completion 문제와, 이를 해결하기 위해 Singular Value Decomposition을 통한 차원 축소 및 내재 공간 학습이 어떤 원리로 이루어 지는지 설명합니다. 그리고 PageRank 등 검색 알고리즘, 머신 러닝의 최적화 문제 등에서의 수학의 중요성을 설명하고자 합니다.

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첨부 '1'
  1. Q-curvature in conformal geometry

  2. Quantitative residual non-vanishing of special values of various L-functions

  3. Quantum Dynamics in the Mean-Field and Semiclassical Regime

  4. Quasi-homomorphisms into non-commutative groups

  5. Random conformal geometry of Coulomb gas formalism

  6. Random matrices and operator algebras

  7. Random walks in spaces of negative curvature

  8. Randomness of prime numbers

  9. Recent progress on the Brascamp-Lieb inequality and applications

  10. 20Oct
    by 김수현
    in 수학강연회

    Recommendation system and matrix completion: SVD and its applications (학부생을 위한 강연)

  11. Regularity for non-uniformly elliptic problems

  12. Regularity theory for non-autonomous elliptic equations in divergence form

  13. Regularity theory for nonlocal equations

  14. Restriction theorems for real and complex curves

  15. Riemann-Hilbert correspondence for irregular holonomic D-modules

  16. Role of Computational Mathematics and Image Processing in Magnetic Resonance Electrical Impedance Tomography (MREIT)

  17. Root multiplicities of hyperbolic Kac-Moody algebras and Fourier coefficients of modular forms

  18. Satellite operators on knot concordance

  19. Seeded Ising Model for Human Iris Templates and Secure Distributed Iris Recognition

  20. Seifert fiberings

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