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Related papers: Infinite-Horizon Ergodic Control via Kernel Mean E…

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We consider a pseudo-marginal Metropolis--Hastings kernel $P_m$ that is constructed using an average of $m$ exchangeable random variables, as well as an analogous kernel $P_s$ that averages $s<m$ of these same random variables. Using an…

Methodology · Statistics 2016-11-01 Chris Sherlock , Alexandre Thiery , Anthony Lee

Decision processes with incomplete state feedback have been traditionally modeled as Partially Observable Markov Decision Processes. In this paper, we present an alternative formulation based on probabilistic regular languages. The proposed…

Optimization and Control · Mathematics 2009-08-07 Ishanu Chattopadhyay , Asok Ray

This paper investigates the consensus problem of general linear multi-agent systems under the framework of optimization. A novel distributed receding horizon control (RHC) strategy for consensus is proposed. We show that the consensus…

Optimization and Control · Mathematics 2014-06-25 Huiping Li , Weisheng Yan

In this paper, motivated by the study of optimal control problems for infinite dimensional systems with endpoint state constraints, we introduce the notion of finite codimensional (exact/approximate) controllability. Some equivalent…

Optimization and Control · Mathematics 2018-10-03 Xu Liu , Qi Lü , Xu Zhang

This article proposes a new approach based on finite-horizon parameterizing manifolds (PMs) for the design of low-dimensional suboptimal controllers to optimal control problems of nonlinear partial differential equations (PDEs) of parabolic…

Optimization and Control · Mathematics 2014-11-19 Mickaël D. Chekroun , Honghu Liu

We introduce a novel contrastive representation learning objective and a training scheme for clinical time series. Specifically, we project high dimensional EHR. data to a closed unit ball of low dimension, encoding geometric priors so that…

Machine Learning · Computer Science 2022-07-05 Thesath Nanayakkara , Gilles Clermont , Christopher James Langmead , David Swigon

This paper proposes a consensus-based distributed nonlinear filter with kernel mean embedding (KME). This fills with gap of posterior density approximation with KME for distributed nonlinear dynamic systems. To approximate the posterior…

Systems and Control · Electrical Eng. & Systems 2023-12-05 Liping Guo , Jimin Wang , Yanlong Zhao , Ji-Feng Zhang

We propose an optimal control framework for persistent monitoring problems where the objective is to control the movement of mobile nodes to minimize an uncertainty metric in a given mission space. For multi agent in a one-dimensional…

Systems and Control · Computer Science 2012-02-29 Christos. G. Cassandras , Xuchao Lin , Xu Chu Ding

This paper proposes a differentiable linear quadratic Model Predictive Control (MPC) framework for safe imitation learning. The infinite-horizon cost is enforced using a terminal cost function obtained from the discrete-time algebraic…

Optimization and Control · Mathematics 2020-01-09 Sebastian East , Marco Gallieri , Jonathan Masci , Jan Koutnik , Mark Cannon

Conditional kernel mean embeddings are nonparametric models that encode conditional expectations in a reproducing kernel Hilbert space. While they provide a flexible and powerful framework for probabilistic inference, their performance is…

Machine Learning · Statistics 2018-11-09 Kelvin Hsu , Richard Nock , Fabio Ramos

This paper proposes an approach, Spectral Dynamics Embedding Control (SDEC), to optimal control for nonlinear stochastic systems. This method reveals an infinite-dimensional feature representation induced by the system's nonlinear…

Machine Learning · Computer Science 2025-08-27 Zhaolin Ren , Tongzheng Ren , Haitong Ma , Na Li , Bo Dai

Kernel interpolation is a fundamental technique for approximating functions from scattered data, with a well-understood convergence theory when interpolating elements of a reproducing kernel Hilbert space. Beyond this classical setting,…

Numerical Analysis · Mathematics 2025-05-19 Toni Karvonen , Gabriele Santin , Tizian Wenzel

We consider the problem of designing finite-horizon safe controllers for a dynamical system for which no explicit analytical model exists and limited data only along a single trajectory of the system are available. Given samples of the…

Optimization and Control · Mathematics 2018-01-15 Mohamadreza Ahmadi , Arie Israel , Ufuk Topcu

The kernel mean embedding of probability distributions is commonly used in machine learning as an injective mapping from distributions to functions in an infinite dimensional Hilbert space. It allows us, for example, to define a distance…

Quantum Physics · Physics 2019-12-24 Jonas M. Kübler , Krikamol Muandet , Bernhard Schölkopf

We present a method for synthesizing controllers to steer trajectories from an initial set to a target set on a finite time horizon. The proposed control synthesis problem is decomposed into two steps. The first step under-approximates the…

Systems and Control · Computer Science 2018-10-02 He Yin , Andrew Packard , Murat Arcak , Pete Seiler

We study multiple ergodic averages along IP sets, meaning we restrict iterates in the averages to all finite sums of some infinite sequence of natural numbers. We give criteria for convergence and divergence in mean of these multiple…

Dynamical Systems · Mathematics 2025-06-24 Bryna Kra , Or Shalom

The paper provides a systematic characterization of quantum ergodic and mixing channels in finite dimensions and a discussion of their structural properties. In particular, we discuss ergodicity in the general case where the fixed point of…

Symmetry-driven phenomena arising in nonlocal metasurfaces supporting quasi-bound states in the continuum (q-BICs) have been opening new avenues to tailor enhanced light-matter interactions via perturbative design principles. Geometric…

Optics · Physics 2023-02-28 Adam Overvig , Yoshiaki Kasahara , Gengyu Xu , Andrea Alù

We examine the limiting behavior of multiple ergodic averages associated with arithmetic progressions whose differences are elements of a fixed integer sequence. For each $\ell$, we give necessary and sufficient conditions under which…

Dynamical Systems · Mathematics 2023-07-24 Nikos Frantzikinakis , Borys Kuca

This paper proposes a novel varying horizon economic model predictive control (EMPC) scheme without terminal constraints for constrained nonlinear systems with additive disturbances and unknown economic costs. The general regression…

Systems and Control · Electrical Eng. & Systems 2025-09-16 Weiliang Xiong , Defeng He , Haiping Du , Jianbin Mu