A problem of great interest in optimization is to minimize a sum of two closed, proper, and convex functions where one is smooth and the other has a …

Calibration parameters in deterministic computer experiments are those attributes that cannot be measured or available in physical experiments. Kenne…

It is a well established result of linear theory that the influence of differing mechanical boundary conditions, i.e., stress-free or no-slip, on the…

The varying-coefficient model is an important nonparametric statistical model that allows us to examine how the effects of covariates vary with expos…

A weak turbulence theory is derived for magnetohydrodynamics under rapid rotation and in the presence of a large-scale magnetic field. The angular ve…

We propose methodology for estimation of sparse precision matrices and statistical inference for their low-dimensional parameters in a high-dimension…

Coherence lengths of one particle states described by quantum wave functions are studied. We show that one particle states in various situations are …

In this paper two types of multgrid methods, i.e., the Rayleigh quotient iteration and the inverse iteration with fixed shift, are developed for solv…

Suppose we are given a matrix that is formed by adding an unknown sparse matrix to an unknown low-rank matrix. Our goal is to decompose the given mat…

The hierarchical triple body approximation has useful applications to a variety of systems from planetary and stellar scales to supermassive black ho…

The present paper develops an optimal linear quadratic boundary controller for $2\times2$ linear hyperbolic partial differential equations (PDEs) wit…

This article provides a Wilsonian description of the perturbatively renormalizable Tensorial Group Field Theory introduced in arXiv:1303.6772 [hep-th…

Inspired by the construction of the Gribov-Zwanziger action in the Landau gauge, we introduce a quark model exhibiting both confinement and chiral sy…

In this paper, inflationary cosmology is reviewed, paying particular attention to its observational signatures associated with large-scale density pe…

We introduce new global and local inexact oracle concepts for a wide class of convex functions in composite convex minimization. Such inexact oracles…

Motivated by the emergence of randomized Krylov space methods for low-rank approximations [34, 43], we presented a ”proof of concept”, that is, structural results for the accuracy of approximate dominant subspaces.

This paper is concerned with approximating the dominant left singular vector space of a real matrix $A$ of arbitrary dimension, from block Krylov spa…

We focus on the downlink of a cellular system, which corresponds to the bulk of the data transfer in such wireless systems. We address the problem of…

We present full accounts of a method to extract nucleon-nucleon (NN) potentials from the Bethe-Salpter amplitude in lattice QCD. The method is applie…

We develop a new proximal-gradient method for minimizing the sum of a differentiable, possibly nonconvex, function plus a convex, possibly non differ…

Procedures in assessing the impact of serial dependency on performance analysis are usually built on parametrically specified models. In this paper, …

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