Zobrazeno 1 - 10
of 200
pro vyhledávání: '"Kon, Mark A."'
Given a directed graph, the Minimal Feedback Arc Set (FAS) problem asks for a minimal set of arcs in a directed graph, which, when removed, results in an acyclic graph. Equivalently, the FAS problem asks to find an ordering of the vertices that minim
Externí odkaz:
http://arxiv.org/abs/2409.16443
Autor:
Root, Jonathan, Kon, Mark
A metric probability space $(\Omega,d)$ obeys the ${\it concentration\; of\; measure\; phenomenon}$ if subsets of measure $1/2$ enlarge to subsets of measure close to 1 as a transition parameter $\epsilon$ approaches a limit. In this paper we conside
Externí odkaz:
http://arxiv.org/abs/2408.02540
Recent advancements in protein docking site prediction have highlighted the limitations of traditional rigid docking algorithms, like PIPER, which often neglect critical stochastic elements such as solvent-induced fluctuations. These oversights can l
Externí odkaz:
http://arxiv.org/abs/2401.11312
Autor:
Mu, Xinying, Kon, Mark
A machine learning (ML) feature network is a graph that connects ML features in learning tasks based on their similarity. This network representation allows us to view feature vectors as functions on the network. By leveraging function operations fro
Externí odkaz:
http://arxiv.org/abs/2401.04874
Given a directed graph, the Minimal Feedback Arc Set (FAS) problem asks for a minimal set of arcs which, when removed, results in an acyclic graph. Equivalently, the FAS problem asks to find an ordering of the vertices that minimizes the number of fe
Externí odkaz:
http://arxiv.org/abs/2401.04187
The nonlinear Poisson-Boltzmann equation (NPBE) is an elliptic partial differential equation used in applications such as protein interactions and biophysical chemistry (among many others). It describes the nonlinear electrostatic potential of charge
Externí odkaz:
http://arxiv.org/abs/2309.16439
Semi-linear elliptic Partial Differential Equations (PDEs) such as the non-linear Poisson Boltzmann Equation (nPBE) is highly relevant for non-linear electrostatics in computational biology and chemistry. It is of particular importance for modeling p
Externí odkaz:
http://arxiv.org/abs/2309.16068
Autor:
Root, Jonathan, Kon, Mark
We consider the sets of negatively associated (NA) and negatively correlated (NC) distributions as subsets of the space $\mathcal{M}$ of all probability distributions on $\mathbb{R}^n$, in terms of their relative topological structures within the top
Externí odkaz:
http://arxiv.org/abs/2304.09737
Autor:
Castrillon-Candas, Julio E, Kon, Mark
Massive vector field datasets are common in multi-spectral optical and radar sensors, among many other emerging areas of application. In this paper we develop a novel stochastic functional (data) analysis approach for detecting anomalies based on the
Externí odkaz:
http://arxiv.org/abs/2207.06229
Autor:
Li, Wenrui, Wang, Xiaoyu, Sun, Yuetian, Milanovic, Snezana, Kon, Mark, Castrillon-Candas, Julio Enrique
Publikováno v:
in IEEE Transactions on Big Data, vol. 10, no. 02, pp. 122-131, 2024
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 methods to datasets involves addressing this problem. However, this is
Externí odkaz:
http://arxiv.org/abs/2110.09680