Low-Rank Matrix Recovery with Side Information

Student: Rizvanov Aydar

Supervisor: Maxim Panov

Educational Programme: Mathematical Methods of Optimization and Stochastics (Master)

Year of Graduation: 2017

Matrix completion problem has been of actual interest within computer science researches nowadays. For instance, recommendation system of such services as Netflix or Tumblr are processing enormous amount of information every day. Collaborative filtering had been one of the most popular ways to estimate unknown parts of the matrices. Inductive matrix completion (IMC) method which is based on Non-negative Matrix Factorization is described, analyzed and developed in the course of the present research.

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