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We consider the problem of optimizing the sum of a smooth, nonconvex function for which derivatives are unavailable, and a convex, nonsmooth function with easy-to-evaluate proximal operator. Of particular focus is the case where the smooth…

Optimization and Control · Mathematics 2024-07-23 Yanjun Liu , Kevin H. Lam , Lindon Roberts

In this paper, we develop a new general approach to the existence and uniqueness theory of infinite dimensional stochastic equations of the form dX+A(t)Xdt = XdW in (0;T)xH, where A(t) is a nonlinear monotone and demicontinuous operator…

Probability · Mathematics 2018-06-18 Viorel Barbu , Michael Röckner

We consider a system of stochastic differential equations driven by a standard n-dimensional Brownian motion where the drift coefficient satisfies a Novikov-type condition while the diffusion coefficient is the identity matrix. We define a…

Probability · Mathematics 2013-07-15 Alberto Lanconelli

We study the numerical solution of nonlinear partially observed optimal stopping problems. The system state is taken to be a multi-dimensional diffusion and drives the drift of the observation process, which is another multi-dimensional…

Optimization and Control · Mathematics 2010-01-20 Mike Ludkovski

In this paper, we consider a stochastic model of incompressible non-Newtonian fluids of second grade on a bounded domain of $\mathbb{R}^2$ with multiplicative noise. We first show that the solutions to the stochastic equations of second…

Probability · Mathematics 2018-04-17 Shijie Shang

Time-varying stochastic optimization problems frequently arise in machine learning practice (e.g. gradual domain shift, object tracking, strategic classification). Although most problems are solved in discrete time, the underlying process…

Machine Learning · Computer Science 2023-02-24 Subha Maity , Debarghya Mukherjee , Moulinath Banerjee , Yuekai Sun

In this paper we propose a second--order method for solving \emph{linear composite sparse optimization problems} consisting of minimizing the sum of a differentiable (possibly nonconvex function) and a nondifferentiable convex term. The…

Optimization and Control · Mathematics 2021-02-15 Pedro Merino , Juan Carlos De Los Reyes

We consider two-point non-self-adjoint boundary eigenvalue problems for linear matrix differential operators. The coefficient matrices in the differential expressions and the matrix boundary conditions are assumed to depend analytically on…

Mathematical Physics · Physics 2010-04-20 Oleg N. Kirillov

To overcome topological constraints and improve the expressiveness of normalizing flow architectures, Wu, K\"ohler and No\'e introduced stochastic normalizing flows which combine deterministic, learnable flow transformations with stochastic…

Machine Learning · Computer Science 2022-12-02 Paul Hagemann , Johannes Hertrich , Gabriele Steidl

Starting from the simple point process model of 1/f noise we derive a stochastic nonlinear differential equation for the signal exhibiting 1/f noise in any desirably wide range of frequency. A stochastic differential equation (the general…

Statistical Mechanics · Physics 2009-11-10 B. Kaulakys , J. Ruseckas

This paper considers a noisy data structure recovery problem. The goal is to investigate the following question: Given a noisy observation of a permuted data set, according to which permutation was the original data sorted? The focus is on…

Information Theory · Computer Science 2020-11-24 Minoh Jeong , Alex Dytso , Martina Cardone , H. Vincent Poor

This paper is concerned with the development and use of duality theory for a nonlinear filtering model with white noise observations. The main contribution of this paper is to introduce a stochastic optimal control problem as a dual to the…

Optimization and Control · Mathematics 2022-08-16 Jin Won Kim , Prashant G. Mehta

We study the choice of the regularisation parameter for linear ill-posed problems in the presence of data noise and operator perturbations, for which a bound on the operator error is known but the data noise-level is unknown. We introduce a…

Numerical Analysis · Mathematics 2018-07-16 Uno Hämarik , Urve Kangro , Stefan Kindermann , Kemal Raik

We consider the covariance steering problem for nonlinear control-affine systems. Our objective is to find an optimal control strategy to steer the state of a system from an initial distribution to a target one whose mean and covariance are…

Optimization and Control · Mathematics 2023-03-27 Hongzhe Yu , Zhenyang Chen , Yongxin Chen

The stochastic differential and integral equations describing the system of particles weakly interacting among themselves which are absorbed and scattered by particles of a medium are considered. The time-dependent transport equation with…

Mathematical Physics · Physics 2010-03-15 Igor Kharin

The problem of optimal estimation of linear functionals constructed from the unobserved values of a stochastic sequence with periodically stationary increments based on observations of the sequence with stationary noise is considered. For…

Statistics Theory · Mathematics 2021-10-18 Maksym Luz , Mikhail Moklyachuk

Stochastic partial differential equations of second order with two unknown parameters are studied. Based on ergodicity, two suitable families of minimum constrast estimators are introduced. Strong consistency and asymptotic normality of…

Probability · Mathematics 2018-06-12 Josef Janak

When high-frequency sound waves travel through media with anomalous diffusion, such as biological tissues, their motion can be described by nonlinear wave equations of fractional higher order. These can be understood as nonlocal…

Analysis of PDEs · Mathematics 2023-10-31 Vanja Nikolić

This paper deals with the resolution of inverse problems in a periodic setting or, in other terms, the reconstruction of periodic continuous-domain signals from their noisy measurements. We focus on two reconstruction paradigms: variational…

Optimization and Control · Mathematics 2018-11-14 Anaïs Badoual , Julien Fageot , Michael Unser

In this paper, we present an optimal filter for linear time-varying continuous-time stochastic systems that simultaneously estimates the states and unknown inputs in an unbiased minimum-variance sense. We first show that the unknown inputs…

Optimization and Control · Mathematics 2016-11-17 Sze Zheng Yong , Minghui Zhu , Emilio Frazzoli
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