arXiv subjects

Zengqi Sun

Publications and source records attributed to Zengqi Sun.

3 recordsLinked to original sources

arXiv2019

Dependence Structure Estimation via Copula

Dependence strucuture estimation is one of the important problems in machine learning domain and has many applications in different scientific areas. In this paper, a theoretical framework for such estimation based on copula and copula entropy -- the probabilistic theory of representation and measurement of statistical dependence, is proposed. Graphical models are considered as a special case of the copula framework. A method of the framework for estimating maximum spanning copula is proposed. Due to copula, the method is irrelevant to the properties of individual variables, insensitive to outlier and able to deal with non-Gaussianity. Experiments on both simulated data and real dataset demonstrated the effectiveness of the proposed method.

cs.LG↗

arXiv2008

Mutual information is copula entropy

We prove that mutual information is actually negative copula entropy, based on which a method for mutual information estimation is proposed.

cs.IT↗

arXiv2007

Copula Component Analysis

A framework named Copula Component Analysis (CCA) for blind source separation is proposed as a generalization of Independent Component Analysis (ICA). It differs from ICA which assumes independence of sources that the underlying components may be dependent with certain structure which is represented by Copula. By incorporating dependency structure, much accurate estimation can be made in principle in the case that the assumption of independence is invalidated. A two phrase inference method is introduced for CCA which is based on the notion of multidimensional ICA.

cs.IR↗