5 accepted papers
The problem of estimating sparse eigenvectors of a symmetric matrix attracts a lot of attention in many applications, especially those with high dimensional data set. While classical eigenvectors can be obtained as the solution of a maximization problem, existing approaches formulated this problem b…
After the 2008 financial crisis, risk management has become more important than performance management and an alternative portfolio design, referred to as risk parity portfolio, has been receiving significant attention from both theoretical and practical fields due to its advantage in diversificatio…
Sequences with low aperiodic autocorrelation sidelobes are well-known to have extensive applications in active sensing and communication systems. In this paper, we consider the sequence design problem of minimizing the ℓp-norm of the autocorrelation side-lobes, which can then be used to minimize the…
In this paper, we start with the standard support vector machine (SVM) formulation and extend it by proposing a general SVM that allows many different variations captured by normalizations in the formulation with very diverse numerical performance. The proposed formulation can not only capture the e…
In this paper, we consider the robust covariance estimation problem in the non-Gaussian set-up. In particular, Tyler's M-estimator is adopted for samples drawn from a heavy-tailed elliptical distribution. For some applications, the covariance matrix naturally possesses certain structure. Therefore,…