We demonstrate a majority-logic decoding algorithm for decoding the generalised hyperoctahedral group Cm wr Sn when thought of as an error-correcting code. We also find the complexity of this decoding algorithm and compare it with that of another, more general, algorithm. Finally, we enumerate the number of error patterns exceeding the correction capability that can be successfully decoded by t...

Instance-based transfer learning methods utilize labeled examples from one domain to improve learning performance in another domain via knowledge transfer. Boosting-based transfer learning algorithms are a subset of such methods and have been applied successfully within the transfer learning community. In this paper, we address some of the weaknesses of such algorithms and extend the most popul...

2 Set up 1 2.1 R code . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 2.1.1 cclust Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 2.1.2 Prediction Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.1.3 Print Function . . . . . . . . . . . . . . . . . . . . . . . . ...

Assume that Alice, Bob and Carol, each of whom privately holds a one-bit input, want to learn the value of the majority function of their inputs without revealing more of their own secret inputs than is necessary. In this paper, we show that such a secure majority computation can be done with a deck of real cards; specifically, the three players can learn only the majority of their inputs using...

We study a collective search process in which tentative proposals arrive sequentially and members of a committee decide whether to accept the current proposal or continue searching. The acceptance decision is made according to a (qualified) majority rule. We study which members have more impact on the decision, as well as the degree of randomness of the decision, as members get patient. When pr...

In recent years, correntropy and its applications in machine learning have been drawing continuous attention owing to its merits in dealing with non-Gaussian noise and outliers. However, theoretical understanding of correntropy, especially in the statistical learning context, is still limited. In this study, within the statistical learning framework, we investigate correntropy based regression ...