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Related papers: Geometry and Duality of Alternating Markov Chains

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This paper studies the estimation of low-rank Markov chains from empirical trajectories. We propose a non-convex estimator based on rank-constrained likelihood maximization. Statistical upper bounds are provided for the Kullback-Leiber…

Machine Learning · Statistics 2018-07-20 Xudong Li , Mengdi Wang , Anru Zhang

Reversible Markov chains play a central role in stochastic modelling and in algorithms such as Markov chain Monte Carlo (MCMC). Motivated by the fundamental importance of reversibility in classical settings, this paper develops a…

Probability · Mathematics 2025-10-28 Damjan Škulj

We consider two types of discrete-time Markov chains where the state space is a graded poset and the transitions are taken along the covering relations in the poset. The first type of Markov chain goes only in one direction, either up or…

Probability · Mathematics 2016-08-06 Kimmo Eriksson , Markus Jonsson , Jonas Sjöstrand

Markov chains are a class of probabilistic models that have achieved widespread application in the quantitative sciences. This is in part due to their versatility, but is compounded by the ease with which they can be probed analytically.…

Machine Learning · Computer Science 2023-12-18 Eddie Seabrook , Laurenz Wiskott

We consider the popular and classical method of alternating projections for finding a point in the intersection of two closed sets. By situating the algorithm in a metric space, equipped only with well-behaved geodesics and angles (in the…

Optimization and Control · Mathematics 2022-06-10 Adrian S. Lewis , Genaro López-Acedo , Adriana Nicolae

The notion of Markov duality between two Markov processes that can live in two different configurations spaces $(x,{\tilde x})$ is revisited via the spectral decompositions of the two Markov generators in their bi-orthogonal basis of right…

Statistical Mechanics · Physics 2025-10-08 Cecile Monthus

Information geometry of Markov chains has been studied using the dually flat structure of the space of transition probabilities. Although applications of this structure have been investigated, few attempts have examined its statistical…

Differential Geometry · Mathematics 2025-11-20 Naomichi Nakajima

Learning the undirected graph structure of a Markov network from data is a problem that has received a lot of attention during the last few decades. As a result of the general applicability of the model class, a myriad of methods have been…

In this work we establish the posterior consistency for a parametrized family of partially observed, fully dominated Markov models. As a main assumption, we suppose that the prior distribution assigns positive probability to all…

Statistics Theory · Mathematics 2016-09-01 Randal Douc , Jimmy Olsson , Francois Roueff

A new object of the probability theory, the two-sided chain of symbols (introduced in Ref. arXiv:physics/0306170) is used to study isotropy properties of binary multi-step Markov chains with the long-range correlations. Established…

Data Analysis, Statistics and Probability · Physics 2015-06-26 S. S. Apostolov , Z. A. Mayzelis , O. V. Usatenko , V. A. Yampol'skii

In this paper, we study consistent and partially exchangeable sequences of Markov chains on a finite state space. We provide a characterisation of the admissible transition rates via a decomposition into individual and coordinated motion of…

We establish two correspondences between reverse-mode automatic differentiation (backpropagation at a given forward-pass point) and compositions of projection maps in Kullback--Leibler (KL) geometry. In both settings, message passing…

Optimization and Control · Mathematics 2026-03-26 Manish Krishan Lal

From the point of view of stochastic analysis the Caputo and Riemann-Liouville derivatives of order $\al \in (0,2)$ can be viewed as (regularized) generators of stable L\'evy motions interrupted on crossing a boundary. This interpretation…

Probability · Mathematics 2022-05-03 Vassili Kolokoltsov

Computational procedures for the stationary probability distribution, the group inverse of the Markovian kernel and the mean first passage times of an irreducible Markov chain, are developed using perturbations. The derivation of these…

Probability · Mathematics 2016-10-12 Jeffrey J. Hunter

In a Hilbert space, we study the strong convergence of alternating projections between two inconsistent affine subspaces with varying relaxation on one side. New convergence results are obtained by seeing the alternating projections as a…

Functional Analysis · Mathematics 2025-07-15 Nguyen T. Thao

This article studies the convergence properties of trans-dimensional MCMC algorithms when the total number of models is finite. It is shown that, for reversible and some non-reversible trans-dimensional Markov chains, under mild conditions,…

Statistics Theory · Mathematics 2024-10-18 Qian Qin

Let $G$ be a finite group. Let $H, K$ be subgroups of $G$ and $H \backslash G / K$ the double coset space. Let $Q$ be a probability on $G$ which is constant on conjugacy classes ($Q(s^{-1} t s) = Q(t)$). The random walk driven by $Q$ on $G$…

Probability · Mathematics 2022-08-24 Persi Diaconis , Arun Ram , Mackenzie Simper

There are several notions of duality between lines and points. In this note, it is shown that all these can be studied in a unified way. Most interesting properties are independent of specific choices. It is also shown that either dual…

Computational Geometry · Computer Science 2025-08-22 Sanjeev Saxena

We argue that the spectral theory of non-reversible Markov chains may often be more effectively cast within the framework of the naturally associated weighted-$L_\infty$ space $L_\infty^V$, instead of the usual Hilbert space $L_2=L_2(\pi)$,…

Probability · Mathematics 2009-06-30 Ioannis Kontoyiannis , Sean P. Meyn

This is a double exposure of the probabilistic construction of Kahler-Einstein metrics on a complex projective algebraic variety X - where the Kahler-Einstein metric emerges from a canonical random point process on X - and the variational…

Differential Geometry · Mathematics 2021-09-02 Robert J. Berman