9 citations · 26 across the 21 of their papers we have counts for
7 papers · 1 filter
Learning to Bound the Multi-class Bayes Error
Salimeh Yasaei Sekeh, Brandon Oselio, Alfred O. Hero
In the context of supervised learning, meta learning uses features, metadata and other information to learn about the difficulty, behavior, or composition of the problem. Using thi…
Convergence Rates for Empirical Estimation of Binary Classification Bounds
Salimeh Yasaei Sekeh, Morteza Noshad, Kevin R. Moon +1
Bounding the best achievable error probability for binary classification problems is relevant to many applications including machine learning, signal processing, and information th…
A Dimension-Independent discriminant between distributions
Salimeh Yasaei Sekeh, Brandon Oselio, Alfred O. Hero
Henze-Penrose divergence is a non-parametric divergence measure that can be used to estimate a bound on the Bayes error in a binary classification problem. In this paper, we show t…
On relative weighted entropies with central moments weight functions
Salimeh Yasaei Sekeh, Adriano Polpo
Following [1], the aim of this paper is to analyze the relative weighted entropy involving the central moments weight functions. We compare the standard relative entropy with the w…
Weighted Gaussian entropy and determinant inequalities
Y. Suhov, S. Yasaei Sekeh, I. Stuhl
We produce a series of results extending information-theoretical inequalities (discussed by Dembo--Cover--Thomas in 1989-1991) to a weighted version of entropy. The resulting inequ…
An extension of the Ky Fan inequality
Yuri Suhov, Salimeh Yasaei Sekeh
The aim of this paper is to analyze the weighted KyFan inequality proposed in [11]. A number of numerical simulations involving the exponential weighted function is given. We show…