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This note presents conjectures on polynomial/algebraic/sub-exponential convergence of transition probabilities for $\lambda$-null recurrent and $\lambda$-transient Markov chains in continuous time. The only known positive examples are in…

Probability · Mathematics 2022-02-14 Phil. Pollett

Generative probabilistic forecasting produces future time series samples according to the conditional probability distribution given past time series observations. Such techniques are essential in risk-based decision-making and planning…

Machine Learning · Computer Science 2024-02-22 Xinyi Wang , Lang Tong , Qing Zhao

Opacity is an information flow property characterizing whether a system reveals its secret to an intruder. Verification of opacity for discrete-event systems modeled by automata is in general a hard problem. We discuss the question whether…

Formal Languages and Automata Theory · Computer Science 2019-12-17 Jiří Balun , Tomáš Masopust

This paper concerns the modeling of multi-way functional data where double or multiple indices are involved. We introduce a concept of weak separability. The weakly separable structure supports the use of factorization methods that…

Methodology · Statistics 2018-11-15 Brian Lynch , Kehui Chen

We study distributional properties of a quadratic form of a stationary functional time series under mild moment conditions. As an important application, we obtain consistency rates of estimators of spectral density operators and prove joint…

Statistics Theory · Mathematics 2022-12-12 Anne van Delft

In this paper, we consider a modified version of a well-known submartingale condition fortheweak convergence of probabilitymeasures, adapted to the semi-Markov case. In this setting, it is convenient to work with an embedded Markov chain…

Probability · Mathematics 2025-12-30 Vitaliy Golomoziy

We study the problem of distributed multi-task learning with shared representation, where each machine aims to learn a separate, but related, task in an unknown shared low-dimensional subspaces, i.e. when the predictor matrix has low rank.…

Machine Learning · Computer Science 2016-03-08 Jialei Wang , Mladen Kolar , Nathan Srebro

In contrast to the usual understanding of probabilistic systems as stochastic processes, recently these systems have also been regarded as transformers of probabilities. In this paper, we give a natural definition of strong bisimulation for…

Logic in Computer Science · Computer Science 2014-05-12 Holger Hermanns , Jan Krčál , Jan Křetínský

This paper studies some analytical properties of weak solutions of 3D stochastic primitive equations with periodic boundary conditions. The martingale problem associated to this model is shown to have a family of solutions satisfying the…

Probability · Mathematics 2017-03-07 Zhao Dong , Rangrang Zhang

We present a general framework for classifying partially observed dynamical systems based on the idea of learning in the model space. In contrast to the existing approaches using model point estimates to represent individual data items, we…

Machine Learning · Statistics 2017-04-19 Yuan Shen , Peter Tino , Krasimira Tsaneva-Atanasova

A stochastic timed automaton is a purely stochastic process defined on a timed automaton, in which both delays and discrete choices are made randomly. We study the almost-sure model-checking problem for this model, that is, given a…

Logic in Computer Science · Computer Science 2015-07-01 Nathalie Bertrand , Patricia Bouyer , Thomas Brihaye , Quentin Menet , Christel Baier , Marcus Groesser , Marcin Jurdzinski

The simplest, and most common, stochastic model for population processes, including those from biochemistry and cell biology, are continuous time Markov chains. Simulation of such models is often relatively straightforward as there are…

Probability · Mathematics 2012-03-01 David F. Anderson , Masanori Koyama

In this paper, we introduce the concept of sparse bilinear logistic regression for decision problems involving explanatory variables that are two-dimensional matrices. Such problems are common in computer vision, brain-computer interfaces,…

Optimization and Control · Mathematics 2014-04-17 Jianing V. Shi , Yangyang Xu , Richard G. Baraniuk

We investigate the application of Weak Poincar\'e Inequalities (WPI) to Markov chains to study their rates of convergence and to derive complexity bounds. At a theoretical level we investigate the necessity of the existence of WPIs to…

Probability · Mathematics 2023-12-20 Christophe Andrieu , Anthony Lee , Sam Power , Andi Q. Wang

A theory of systems with long-range correlations based on the consideration of binary N-step Markov chains is developed. In our model, the conditional probability that the i-th symbol in the chain equals zero (or unity) is a linear function…

Data Analysis, Statistics and Probability · Physics 2007-05-23 O. V. Usatenko , V. A. Yampol'skii

Discrete Markov random fields form a natural class of models to represent images and spatial data sets. The use of such models is, however, hampered by a computationally intractable normalising constant. This makes parameter estimation and…

Computation · Statistics 2015-05-25 Haakon Michael Austad , Håkon Tjelmeland

Looking at bivariate copulas from the perspective of conditional distributions and considering weak convergence of almost all conditional distributions yields the notion of weak conditional convergence. At first glance, this notion of…

Statistics Theory · Mathematics 2020-10-12 Thimo M. Kasper , Sebastian Fuchs , Wolfgang Trutschnig

Taking matrix as a synonym for a numerical function on the Cartesian product of two (in general, infinite) sets, a simple purely algebraic "reciprocity property" says that the set of rows spans a finite-dim space iff the set of columns does…

Functional Analysis · Mathematics 2008-08-29 Eliahu Levy

The notion of a successful coupling of Markov processes, based on the idea that both components of the coupled system ``intersect'' in finite time with probability one, is extended to cover situations when the coupling is unnecessarily…

Probability · Mathematics 2007-05-23 Michael Blank , Sergey Pirogov

We study the computational complexity of various problems related to synchronization of weakly acyclic automata, a subclass of widely studied aperiodic automata. We provide upper and lower bounds on the length of a shortest word…

Formal Languages and Automata Theory · Computer Science 2017-12-08 Andrew Ryzhikov
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