A novel approach for event summarization and rare event detection is proposed. Unlike conventional methods that deal with event summarization and rare event detection independently...
In this paper, we present the use of Markov Chain Monte Carlo (MCMC) methods to attack the classical ciphers. We use frequency analysis as our basic tool. First we investigate the...
We propose a novel way to induce a random field from an energy function on discrete labels. It amounts to locally injecting noise to the energy potentials, followed by finding t...
In the database community, work on information extraction (IE) has centered on two themes: how to effectively manage IE tasks, and how to manage the uncertainties that arise in th...
Daisy Zhe Wang, Michael J. Franklin, Minos N. Garo...
Slice sampling provides an easily implemented method for constructing a Markov chain Monte Carlo (MCMC) algorithm. However, slice sampling has two major drawbacks: (i) it requires...
One of the main shortcomings of Markov chain Monte Carlo samplers is their inability to mix between modes of the target distribution. In this paper we show that advance knowledge ...
— In many visual multi-object tracking applications, the question when to add or remove a target is not trivial due to, for example, erroneous outputs of object detectors or obse...
In this paper we present Poisson sum series representations for α-stable (αS) random variables and α-stable processes, in particular concentrating on continuous-time autoregres...
This paper investigates a Bayesian model and a Markov chain Monte Carlo (MCMC) algorithm for gene factor analysis. Each sample in the dataset is decomposed as a linear combination...
Cecile Bazot, Nicolas Dobigeon, Jean-Yves Tournere...
This paper addresses the problem of estimating the statistical distribution of multiple-tissue non-stationary ultrasound images of skin. The distribution of multiple-tissue images...
Marcelo Pereyra, Nicolas Dobigeon, Hadj Batatia, J...