, detection of genes that are most involved is vital and crucial. In this article, we propose a Maximum–Minimum Correntropy Criterion (MMCC) approach for selection of informative genes from microarray data sets which is stable, fast and robust against diverse...

index based on correntropy spectral density. Here, the correntropy function was defined as a sum of weighted positive definite kernels. Optimal weights were found by solving a quadratic optimization problem. In order to evaluate the proposed approach...

This paper presents a general half quadratic framework for simultaneous analysis of the whole array com-

parative genomic hybridization (aCGH) profiles in a data set. The proposed framework accommodates

different ...

-Gaussian

noise/interference assumption, the optimal detector will be impractically complex.

Therewith, inspired by the optimal maximum likelihood detector, a suboptimal

detector is designed. In particular, a novel detector based on the generalized

correntropy, which...

This paper presents a new method for analyzing Array comparative genomic hybridization (aCGH) data

based on Correntropy. A new formulation based on low-rank aCGH data and Correntropy is proposed and

its solution is presented based...

contribute in problems that several

clusters of interconnected agents are interested in learning multiple tasks. To

address multitask learning problem, we consider an information theoretic criterion

called correntropy in a distributed...

One of the most significant issues in machine learning is system identification with many applications, e.g., channel estimation (CE) in digital communications. Introducing a new correntropy-based method, this paper deals with the comparison between...

, we

estimate the probability distribution of each criterion in order

to accommodation to the criteria value uncertainty. Finally, by

utilizing the generalized correlation function, i.e. correntropy, we

study the statistical...

) criteria in

nonGaussian environments, we propose a linearly constrained

version of maximum correntropy learning algorithm in order

to solve beamforming problem in presence of nonGaussian and

impulsive noises. Simulation results...

-theoretic similarity measure known as correntropy is exploited by each local sensor, (ii) for transmitting local decisions, an estimation of apriori probabilities is used by local sensors, and (iii) for optimizing power allocation to each sensor, the Bhattacharyya...