We propose a new robust estimator for parameter estimation in highly noisy data with multiple structures and without prior information on the noise scale of inliers. This is a diag...
Trung Ngo Thanh, Hajime Nagahara, Ryusuke Sagawa, ...
The aim of this paper is to apply the concept of robust optimization introduced by Bel-Tal and Nemirovski to the portfolio selection problems based on multi-stage scenario trees. ...
Background: Nonlinear regression, like linear regression, assumes that the scatter of data around the ideal curve follows a Gaussian or normal distribution. This assumption leads ...
An integrated modeling and robust model predictive control (MPC) approach is proposed for a class of nonlinear systems with unknown steady state. First, the nonlinear system is id...
Hui Peng, Zi-Jiang Yang, Weihua Gui, Min Wu, Hideo...
Value-at-Risk (VaR) is one of the most widely accepted risk measures in the financial and insurance industries, yet efficient optimization of VaR remains a very difficult problem....