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 …

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

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

The problem of finding sparse solutions to underdetermined systems of linear equations arises in several applications (e.g. signal and image processi…

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

A general framework is developed to investigate the properties of useful choices of stationary spacelike slicings of stationary spacetimes whose cong…

We study locking of the modulation frequency of a relative periodic orbit in a general $S^1$-equivariant system of ordinary differential equations un…

In this paper, a new approach based on convex analysis is introduced to solve the $H_\infty$ problem for discrete-time nonlinear stochastic systems. …

Atmospheric turbulence is an important limit to high angular resolution in astronomy. Interferometry resolved this issue by filtering the incoming li…

Rational large Reynolds number matched asymptotic analyses of three-dimensional magneto-hydrodynamic dynamo states are concerned. The dynamos, here a…

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…

For unconstrained control problems, a local convergence rate is established for an $hp$-method based on collocation at the Radau quadrature points in…

A classical problem in matrix computations is the efficient and reliable approximation of a given matrix by a matrix of lower rank. The truncated sin…

Recently, deep learning approaches with various network architectures have achieved significant performance improvement over existing iterative recon…

In this paper, two robust model predictive control (MPC) schemes are proposed for tracking control of nonholonomic systems with bounded disturbances:…

In this paper, using the linearization technique we write the Helmholtz transmission eigenvalue problem as an equivalent nonselfadjoint linear eigenv…

Elastic-scattering phase shifts for four-nucleon systems are studied in an $ab$-$initio$ type cluster model in order to clarify the role of the tenso…

The traditional difficulty about stochastic singular control is to characterize the regularities of the value function and the optimal control policy…

A local convergence rate is established for a Gauss orthogonal collocation method applied to optimal control problems with control constraints. If th…

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