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We study the so-called two-time-scale stochastic approximation, a simulation-based approach for finding the roots of two coupled nonlinear operators. Our focus is to characterize its finite-time performance in a Markov setting, which often…

Optimization and Control · Mathematics 2021-04-06 Thinh T. Doan

In the hard-core model on a finite graph we are given a parameter lambda>0, and an independent set I arises with probability proportional to lambda^|I|. On infinite graphs a Gibbs distribution is defined as a suitable limit with the correct…

Combinatorics · Mathematics 2016-11-04 Antonio Blanca , David Galvin , Dana Randall , Prasad Tetali

This paper proposes a multilayer graph model for the community detection from multiple observations. This is a very frequent situation, when different estimators are applied to infer graph edges from signals at its nodes, or when different…

Neurons and Cognition · Quantitative Biology 2024-10-23 Tiziana Cattai , Gaetano Scarano , Marie-Constance Corsi , Fabrizio De Vico Fallani , Stefania Colonnese

We propose a novel method for the determination of the effective interaction potential between the amino acids of a protein. The strategy is based on the combination of a new optimization procedure and a geometrical argument, which also…

Soft Condensed Matter · Physics 2009-10-31 Jort van Mourik , Cecilia Clementi , Amos Maritan , Flavio Seno , J. R. Banavar

We study the N-step binary stationary ergodic Markov chain and analyze its differential entropy. Supposing that the correlations are weak we express the conditional probability function of the chain through the pair correlation function and…

Statistical Mechanics · Physics 2015-06-24 S. S. Melnik , O. V. Usatenko

\emph{Maximal ancestral graph} (MAGs) is a class of graphical model that extend the famous \emph{directed acyclic graph} in the presence of latent confounders. Most score-based approaches to learn the unknown MAG from empirical data rely on…

Machine Learning · Statistics 2024-02-08 Zhongyi Hu , Robin Evans

In this paper an original interacting particle system approach is developed for studying Markov chains in rare event regimes. The proposed particle system is theoretically studied through a genealogical tree interpretation of Feynman--Kac…

Probability · Mathematics 2007-05-23 Pierre Del Moral , Josselin Garnier

While theories postulating a dual cognitive system take hold, quantitative confirmations are still needed to understand and identify interactions between the two systems or conflict events. Eye movements are among the most direct markers of…

Neurons and Cognition · Quantitative Biology 2020-02-27 Alessandro Rossi , Sara Ermini , Dario Bernabini , Dario Zanca , Marino Todisco , Alessandro Genovese , Antonio Rizzo

We focus on the parametric estimation of the distribution of a Markov environment from the observation of a single trajectory of a one-dimensional nearest-neighbor path evolving in this random environment. In the ballistic case, as the…

Statistics Theory · Mathematics 2015-04-15 Pierre Andreoletti , Dasha Loukianova , Catherine Matias

We consider a countable system of interacting (possibly non-Markovian) stochastic differential equations driven by independent Brownian motions and indexed by the vertices of a locally finite graph $G = (V,E)$. The drift of the process at…

Probability · Mathematics 2020-09-28 Daniel Lacker , Kavita Ramanan , Ruoyu Wu

The linking genotype to phenotype is the fundamental aim of modern genetics. We focus on study of links between gene expression data and phenotype data through integrative analysis. We propose three approaches. 1) The inherent complexity of…

Quantitative Methods · Quantitative Biology 2015-06-30 Min Xu

We propose a scalable semiparametric Bayesian model to capture dependencies among multiple neurons by detecting their co-firing (possibly with some lag time) patterns over time. After discretizing time so there is at most one spike at each…

Applications · Statistics 2015-06-22 Babak Shahbaba , Bo Zhou , Shiwei Lan , Hernando Ombao , David Moorman , Sam Behseta

The two-point central difference is a common algorithm in biological signal processing and is particularly useful in analyzing physiological signals. In this paper, we develop a model-based classification method to detect epileptic seizures…

Applications · Statistics 2020-06-01 Antonio Quintero-Rincon , Carlos D'Giano , Hadj Batatia

We propose a general method to study dependent data in a binary tree, where an individual in one generation gives rise to two different offspring, one of type 0 and one of type 1, in the next generation. For any specific characteristic of…

Probability · Mathematics 2009-09-29 Julien Guyon

We propose a novel, tractable latent state inference scheme for Markov jump processes, for which exact inference is often intractable. Our approach is based on an entropic matching framework that can be embedded into the well-known…

Machine Learning · Computer Science 2026-02-27 Yannick Eich , Bastian Alt , Heinz Koeppl

Gene expression of social actions in Drosophilae has been attracting wide interest from biologists, medical scientists and psychologists. Gene-edited Drosophilae have been used as a test platform for experimental investigation. For example,…

Computer Vision and Pattern Recognition · Computer Science 2019-09-12 Khan Faraz , Ahmed Bouridane , Richard Jiang , Tiancheng Xia , Paul Chazot , Abdel Ennaceur

Direct imaging searches for exoplanets around stars detect many spurious candidates that are in fact background field stars. To help distinguish these from genuine companions, multi-epoch astrometry can be used to identify a common proper…

Earth and Planetary Astrophysics · Physics 2023-12-11 Philipp Herz , Matthias Samland , Coryn A. L. Bailer-Jones

The evolutionary effect of recombination depends crucially on the epistatic interactions between linked loci. A paradigmatic case where recombination is known to be strongly disadvantageous is a two-locus fitness landscape dis- playing…

Populations and Evolution · Quantitative Biology 2012-02-13 Su-Chan Park , Joachim Krug

We introduce a method called neighbor-based bootstrapping (NB2) that can be used to quantify the geospatial variation of a variable. We applied this method to an analysis of the incidence rates of disease from electronic medical record data…

Methodology · Statistics 2017-03-07 Maria T Patterson , Robert L Grossman

The problem of detection and possible estimation of a signal generated by a dynamic system when a variable number of noisy measurements can be taken is here considered. Assuming a Markov evolution of the system (in particular, the pair…

Information Theory · Computer Science 2022-05-12 Emanuele Grossi , Marco Lops