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Extra Form
Lecturer 정교민
Dept. 서울대 전기공학부
date Oct 16, 2014
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.

Atachment
Attachment '1'
  1. Random conformal geometry of Coulomb gas formalism

  2. Random matrices and operator algebras

  3. Random walks in spaces of negative curvature

  4. Randomness of prime numbers

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

  6. 20Oct
    by 김수현
    in Math Colloquia

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

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

  8. Restriction theorems for real and complex curves

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

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

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

  12. Satellite operators on knot concordance

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

  14. Seifert fiberings

  15. Seoul ICM 2014 유치과정 개요 및 준비전략

  16. Sheaf quantization of Hamiltonian isotopies and non-displacability problems

  17. Solver friendly finite element methods

  18. Space.Time.Noise

  19. Spectral Analysis for the Anomalous Localized Resonance by Plasmonic Structures

  20. Structures of Formal Proofs

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