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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. Structural stability of meandering-hyperbolic group actions

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

  3. Space.Time.Noise

  4. Solver friendly finite element methods

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

  6. Seoul ICM 2014 유치과정 개요 및 준비전략

  7. Seifert fiberings

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

  9. Satellite operators on knot concordance

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

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

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

  13. Restriction theorems for real and complex curves

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

  15. Regularity for non-uniformly elliptic problems

  16. 20Oct
    by 김수현
    in Math Colloquia

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

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

  18. Randomness of prime numbers

  19. Random walks in spaces of negative curvature

  20. Random matrices and operator algebras

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