22 citations · 78 across the 23 of their papers we have counts for
23 papers
The Topology of Negatively Associated Distributions
Jonathan Root, Mark Kon
We consider the sets of negatively associated (NA) and negatively correlated (NC) distributions as subsets of the space of all probability distributions on $\mathbb{R…
Distribution-Free Stochastic Analysis and Robust Multilevel Vector Field Anomaly Detection
Julio E Castrillon-Candas, Michael Rosenbaum, Mark Kon
Massive vector field datasets are common in multi-spectral optical and radar sensors, among many other emerging areas of application. We develop a novel stochastic functional (data…
Multilevel Stochastic Optimization for Imputation in Massive Medical Data Records
Wenrui Li, Xiaoyu Wang, Yuetian Sun +3
It has long been a recognized problem that many datasets contain significant levels of missing numerical data. A potentially critical predicate for application of machine learning…
Stochastic tensor space feature theory with applications to robust machine learning
Julio Enrique Castrillon-Candas, Kaili Shi, Dingning Liu +5
In this paper we develop a Multilevel Orthogonal Subspace (MOS) Karhunen--Loève feature theory based on stochastic tensor spaces, for the construction of robust machine learning fe…
Existence of Strong Solution for the Complexified Non-linear Poisson Boltzmann Equation
Brian Choi, Jie Xu, Trevor Norton +2
We prove the existence and uniqueness of the complexified Nonlinear Poisson-Boltzmann Equation (nPBE) in a bounded domain in . The nPBE is a model equation in nonline…
Continuum Limits of the 1D Discrete Time Quantum Walk
Michael Manighalam, Mark Kon
The discrete time quantum walk (DTQW) is a universal quantum computational model. Significant relationships between discrete and corresponding continuous quantum systems have been…