1,721,055 research outputs found
Stochastic Model of Automatic Traffic Service Controlled by Lattice Coulomb Interactions
Get PDFWe define a model for a system of automatic vehicles (cybercars) circulating on arbitrary planar closed road-networks. The demands for transportation arrive according to a Poisson flow. The diffusion of cybercars along the network is influenced by Coulomb forces, determined by the distribution of clients in the system. This model is implemented numerically on a had-hoc graphical interface, using Monte-Carlo methods. In this way the the Coulomb forces algorithm, used to optimize the service, seems to be quite efficient. Preliminary numerical results are presented for this model, together with a phase diagram
Approximate Inverse Ising models close to a Bethe Reference Point
Get PDFInternational audienceWe investigate different ways of generating approximate solutions to the inverse Ising problem. Our approach consists in to take as a starting point for further perturbation procedures, a Bethe mean-field solution obtained with a maximum spanning tree of pairwise mutual information which we refer to as the "Bethe reference point". We consider three different ways of following this idea: in the first one, we discuss a greedy procedure by which optimal links to be added starting from the Bethe reference point are selected and calibrated iteratively; the second one is based on the observation that the natural gradient can be computed analytically at the Bethe point; the last one deals with loop corrections to the Bethe point. Assuming no external field and using a dual transform we develop a dual loop joint model based on a well-chosen cycle basis. This leads us to identify a subclass of planar models, which we refer to as \emph{dual-loop-free models}, having possibly many loops, but characterized by a singly connected dual factor graph, for which the partition function and the linear response can be computed exactly in respectively O(N) and O(N^2) operations, thanks to a dual weight propagation message passing procedure that we set up. When restricted to this subclass of models, the inverse Ising problem being convex, becomes tractable at any temperature. Numerical experiments show that this can serve to some extent as a good approximation for models with dual loops
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Pairwise MRF Models Selection for Traffic Inference
Get PDFInternational audienceWe survey some recent work where, motivated by traffic inference, we design in parallel two concurrent models, an Ising and a Gaussian ones, with the constraint that they are suitable for ''belief-propagation'' based inference. In order to build these model, we study how a Bethe mean-field solution to inverse problems obtained with a maximum spanning tree of pairwise mutual information, can serve as a reference point for further perturbation procedures. We consider three different ways along this idea: the first one is based on an explicit natural gradient formula; the second one is a link by link construction based on iterative proportional scaling; the last one relies on a duality transformation leading to a loop correction propagation algorithm on a dual factor graph
Stochastic Model of Automatic Traffic Service Controlled by Lattice Coulomb Interactions
No full textWe define a model for a system of automatic vehicles (cybercars) circulating on arbitrary planar closed road-networks. The demands for transportation arrive according to a Poisson flow. The diffusion of cybercars along the network is influenced by Coulomb forces, determined by the distribution of clients in the system. This model is implemented numerically on a had-hoc graphical interface, using Monte-Carlo methods. In this way the the Coulomb forces algorithm, used to optimize the service, seems to be quite efficient. Preliminary numerical results are presented for this model, together with a phase diagram
An Ising Model for Road Traffic Inference
Get PDFInternational audienceWe review some properties of the ''belief propagation'' algorithm, a distributed iterative map, used to perform Bayesian inference and present some recent work where this algorithm serves as a starting point to encode observation data into a probabilistic model and to process large scale information in real time. A natural approach is based on the linear response theory and various recent instantiations are presented. We will focus on the particular situation where the data have many different statistical components, representing a variety of independent patterns. As an application, the problem of reconstructing and predicting traffic states based on floating car data is then discussed.Nous passons en revue quelques propriétés de l'algorithme de "propagation de croyances", un algorithme distribué itératif, utilisé pour effectuer des tâches d'inférence Bayésienne, et nous présentons des travaux récents où cet algorithme sert de point de départ à la fois pour encoder des données d'observation dans un modèle probabiliste et pour traiter une grande quantité d'information en temps réel. Une approche naturelle est basée sur le théorie de la réponse linéaire et des mises en oeuvre récentes sont présentées. Nous nous concentrons en particulier sur la situation où les données correspondent à une disribution multi-modale, chacun des modes représentant des patrons indépendants. En guise d'application, nous discutons le problème de reconstruction et de prédiction de trafic, basé sur des données flottantes
Free Dynamics of Feature Learning Processes
No full textInternational audienceRegression models usually tend to recover a noisy signal in the form of a combination of regressors, also called features in machine learning, themselves being the result of a learning process. The alignment of the prior covariance feature matrix with the signal is known to play a key role in the generalization properties of the model, i.e. its ability to make predictions on unseen data during training. We present a statistical physics picture of the learning process. First we revisit the ridge regression to obtain compact asymptotic expressions for train and test errors, rendering manifest the conditions under which efficient generalization occurs. It is established thanks to an exact test-train sample error ratio combined with random matrix properties. Along the way in the form of a self-energy emerges an effective ridge penalty-precisely the train to test error ratio-which offer a very simple parameterization of the problem. This formulation appears convenient to tackle the learning process of the feature matrix itself. We derive an autonomous dynamical system in terms of elementary degrees of freedom of the problem determining the evolution of the relative alignment between the population matrix and the signal. A macroscopic counterpart of these equations is also obtained and various dynamical mechanisms are unveiled, allowing one to interpret the dynamics of simulated learning processes and reproduce trajectories of single experimental run with high precision
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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