3 accepted papers
This paper presents a new framework for robust regression analysis. Under this framework, the input-output relation of a system is inferred by minimizing a new robust loss which relates the outputs to a presumed parametric function of the inputs. The considered loss arises from a modified version of…
In this paper we present a new divergence, called $\mathcal{K}$-divergence, that involves a weighted version of the hypothesized log-likelihood function. To down-weight low density areas, attributed to outliers, the corresponding weight function is a convolved version of the underlying density with…
In this paper, we develop a new robust spectrum sensing method for MIMO cognitive radios in the presence of heavy-tailed noise. The proposed sensing technique, called measure-transformed covariance test (MTCT), operates by applying a transform to the probability measure of the data. The considered p…