Search results for "Markov"
showing 10 items of 628 documents
Concurrent photo sequence organization
2012
Personal photo album organization is a highly demanding domain where advanced tools are required to manage large photo collections. In contrast to many previous works, that try to solve the problem of organizing a single user photo sequence, we present a new technique to account for the concurrent photo sequence organization problem, that is the problem of organizing multiple photo sequences taken during the same event. Given a set of sequences acquired at the same place during the same temporal window by several users using different cameras, our framework is intended to capture the evolution of the event and groups photos based on temporal proximity and visual content. The method automati…
Hankelet-based dynamical systems modeling for 3D action recognition
2015
This paper proposes to model an action as the output of a sequence of atomic Linear Time Invariant (LTI) systems. The sequence of LTI systems generating the action is modeled as a Markov chain, where a Hidden Markov Model (HMM) is used to model the transition from one atomic LTI system to another. In turn, the LTI systems are represented in terms of their Hankel matrices. For classification purposes, the parameters of a set of HMMs (one for each action class) are learned via a discriminative approach. This work proposes a novel method to learn the atomic LTI systems from training data, and analyzes in detail the action representation in terms of a sequence of Hankel matrices. Extensive eval…
Comprehensive Uncertainty Management in MDPs
2013
Multistage decision-making in robots involved in real-world tasks is a process affected by uncertainty. The effects of the agent’s actions in a physical en- vironment cannot be always predicted deterministically and in a precise manner. Moreover, observing the environment can be a too onerous for a robot, hence not continuos. Markov Decision Processes (MDPs) are a well-known solution inspired to the classic probabilistic approach for managing uncertainty. On the other hand, including fuzzy logics and possibility theory has widened uncertainty representa- tion. Probability, possibility, fuzzy logics, and epistemic belief allow treating dif- ferent and not always superimposable facets of unce…
Simple epidemic model by a Markov chain
2008
In this paper we propose a continuous-time Markov chain to describe a SIs model with and without external reinfection
Diffusion modeling of COVID-19 under lockdown
2021
Viral immune evasion by sequence variation is a significant barrier to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine design and coronavirus disease-2019 diffusion under lockdown are unpredictable with subsequent waves. Our group has developed a computational model rooted in physics to address this challenge, aiming to predict the fitness landscape of SARS-CoV-2 diffusion using a variant of the bidimensional Ising model (2DIMV) connected seasonally. The 2DIMV works in a closed system composed of limited interaction subjects and conditioned by only temperature changes. Markov chain Monte Carlo method shows that an increase in temperature implicates reduced virus diffusi…
Fiscal Policy and Asset Price Cycles: Evidence from Four European Countries
2014
OS; International audience; We test for non-linear effects of asset prices on the fiscal policy of four major European economies (France, Italy, Spain and UK). We model government spending and revenue as time-varying transition probability Markovian processes (TVPMS), and find that: (i) in France and Italy, the impact of housing prices on government revenue is conditioned by the phase of the stock price cycle; (ii) a similar asymmetric pattern is found for the UK when considering the effect of stock price fluctuations on government revenue and spending vis-à-vis the troughs and peaks of aggregate wealth; and (iii) for Spain, a fall in government revenue is typically associated with a negati…
Short-run and long-run persistence of bad health among elderly
2019
We study the health dynamics among older Americans using ten waves of the Health and Retirement Study following a spell-approach and a regression-based approach. The former is fully non parametric synthesizing the sequences of health status into a Health Persistence Index. The latter approach relies on a Latent Markov (LM) model capturing persistence in poor health by modelling time-varying unobserved heterogeneity. Our results show that only few elders experiences persistently a poor health status. The higher values of the index are consistently observed with the main socio-demo-economic risk factors. Moreover LM model indicates the existence of three unobserved groups differing in their p…
Analysis of clickstream data with mixture hidden markov models
2021
clickstream data sono un’importante fonte di informazioni per l’ecommerce, sebbene non siano semplici da gestire e convertire queste informazioni in un reale vantaggio competitivo non e un compito banale. In questo articolo, consid- ` eriamo l’applicazione dei mixture hidden Markov model a dati relativi al flusso di clickstream estratti dal portale e-commerce di un’azienda di servizi turistici. Sono stati individuati cluster relativi al comportamento di navigazione degli utenti e alla loro posizione geografica che forniscono indicazioni importanti per lo sviluppo di nuove strategie di business. Clickstream data is an important source of information for businesses, however it is not easy to …
Particle Group Metropolis Methods for Tracking the Leaf Area Index
2020
Monte Carlo (MC) algorithms are widely used for Bayesian inference in statistics, signal processing, and machine learning. In this work, we introduce an Markov Chain Monte Carlo (MCMC) technique driven by a particle filter. The resulting scheme is a generalization of the so-called Particle Metropolis-Hastings (PMH) method, where a suitable Markov chain of sets of weighted samples is generated. We also introduce a marginal version for the goal of jointly inferring dynamic and static variables. The proposed algorithms outperform the corresponding standard PMH schemes, as shown by numerical experiments.
Observer-based finite-time fuzzy H∞ control for discrete-time systems with stochastic jumps and time-delays
2014
This paper is concerned with the problem of observer-based finite-time H ∞ control for a family of discrete-time Markovian jump nonlinear systems with time-delays represented by Takagi-Sugeno (T-S) model. The main contribution of this paper is to design an observer-based finite-time H ∞ controller such that the resulting closed-loop system is stochastic finite-time bounded and satisfies a prescribed H ∞ disturbance attenuation level over the given finite-time interval. Sufficient criteria on stochastic finite-time H ∞ stabilization via observer-based fuzzy state feedback are presented for the solvability of the problem, which can be tackled by a feasibility problem in terms of linear matrix…