Data Science and Matrix Optimization-课程推荐
课程介绍：Data science is a "concept to unify statistics, data analysis, machine learning and their related methods" in order to "understand and analyze actual phenomena" with data1. With the development of the technologies of data collection and storage, big data emerges from various fields. It brings great opportunities for researchers. Many algorithms have been proposed , and most of them involve intensive matrix optimization techniques. This course covers ten important topics of “Data Science” (one topic per week). It is intended to teach mathematical models, matrix optimization models, algorithms and applications related to ten basic problems from practical problems and real-world data. This course is designed for doctoral, postgraduate and upper-level undergraduate students in all majors.
The ten topics and the corresponding material are as follows:
Robust PCA
Non-negative Matrix Factorization
Matrix Completion
Sparse Coding
Sparse Sensing
Subspace Clustering
Precision Matrix Estimation
Nonlinear Manifold Learning
Manifold Alignment
Tensor Factorization
