Academic literature on the topic 'Tenseurs de bas rang'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Tenseurs de bas rang.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Journal articles on the topic "Tenseurs de bas rang"
Clément, Virginie, Jean-Paul Poivey, O. Fougère, Emmanuel Tillard, Renaud Lancelot, A. Gueye, Didier Richard, and Bernard Bibé. "Etude de la variabilité des caractères de reproduction chez les petits ruminants en milieu d'élevage traditionnel au Sénégal." Revue d’élevage et de médecine vétérinaire des pays tropicaux 50, no. 3 (March 1, 1997): 235–49. http://dx.doi.org/10.19182/remvt.9576.
Full textVissoh, Durand Gbègnimon Ulrich, Luc Hippolyte Dossa, Sanni Yô Doko Allou, and Armand Bienvenu Gbangboche. "Production de lait de la chèvre Alpine élevée au Sud Bénin : effet du mois de mise bas, de la parité et du poids post-partum." Revue d’élevage et de médecine vétérinaire des pays tropicaux 74, no. 3 (September 30, 2021): 161–65. http://dx.doi.org/10.19182/remvt.36747.
Full textPrioux, France. "Mouvement saisonnier des naissances : influence du rang et de la légitimité dans quelques pays d'Europe occidentale." Population Vol. 43, no. 3 (March 1, 1988): 587–609. http://dx.doi.org/10.3917/popu.p1988.43n3.0609.
Full textDerruau, Max. "À l’origine du « rang » canadien." Cahiers de géographie du Québec 1, no. 1 (April 12, 2005): 39–47. http://dx.doi.org/10.7202/020004ar.
Full textPrioux, France. "La fécondité par rang de naissance dans les générations : évolution comparée en Angleterre-Galles et aux Pays-Bas, depuis la génération 1930." Population Vol. 43, no. 4 (April 1, 1988): 855–76. http://dx.doi.org/10.3917/popu.p1988.43n4-5.0876.
Full textALEXANDRE, G., G. AUMONT, J. FLEURY, J. C. MAINAUD, and T. KANDASSAMY. "Performances zootechniques de la chèvre Créole allaitante de Guadeloupe. Bilan de 20 ans dans un élevage expérimental de l’INRA." INRAE Productions Animales 10, no. 1 (February 7, 1997): 7–20. http://dx.doi.org/10.20870/productions-animales.1997.10.1.3973.
Full textQuirin, René, T. M. Léal, and C. Guimaraes Filho. "Epidémiologie descriptive des avortements caprins en élevage traditionnel du Nordeste brésilien. Enquête rétrospective de carrières de femelles." Revue d’élevage et de médecine vétérinaire des pays tropicaux 46, no. 3 (March 1, 1993): 495–502. http://dx.doi.org/10.19182/remvt.9455.
Full textMourad, M., and S. Rashwan. "Production laitière des buffles et cause de mortalité des veaux dans un système de production semi-intensif en Egypte." Revue d’élevage et de médecine vétérinaire des pays tropicaux 54, no. 2 (February 1, 2001): 139. http://dx.doi.org/10.19182/remvt.9792.
Full textCortese, Ennio. "Une carrière byzantine de Charlemagne. Échos de droit vulgaire romano-gothique au Moyen Âge." Mélanges de l École française de Rome Moyen Âge 113, no. 2 (2001): 857–68. http://dx.doi.org/10.3406/mefr.2001.9165.
Full textLaffargue, Jean-Pierre. "Effets et financement d'une réduction des charges sur les bas salaires." Revue économique 51, no. 3 (May 1, 2000): 489–98. http://dx.doi.org/10.3917/reco.p2000.51n3.0489.
Full textDissertations / Theses on the topic "Tenseurs de bas rang"
Liu, Zhenjiao. "Incomplete multi-view data clustering with hidden data mining and fusion techniques." Electronic Thesis or Diss., Institut polytechnique de Paris, 2023. http://www.theses.fr/2023IPPAS011.
Full textIncomplete multi-view data clustering is a research direction that attracts attention in the fields of data mining and machine learning. In practical applications, we often face situations where only part of the modal data can be obtained or there are missing values. Data fusion is an important method for incomplete multi-view information mining. Solving incomplete multi-view information mining in a targeted manner, achieving flexible collaboration between visible views and shared hidden views, and improving the robustness have become quite challenging. This thesis focuses on three aspects: hidden data mining, collaborative fusion, and enhancing the robustness of clustering. The main contributions are as follows:1. Hidden data mining for incomplete multi-view data: existing algorithms cannot make full use of the observation of information within and between views, resulting in the loss of a large amount of valuable information, and so we propose a new incomplete multi-view clustering model IMC-NLT (Incomplete Multi-view Clustering Based on NMF and Low-Rank Tensor Fusion) based on non-negative matrix factorization and low-rank tensor fusion. IMC-NLT first uses a low-rank tensor to retain view features with a unified dimension. Using a consistency measure, IMC-NLT captures a consistent representation across multiple views. Finally, IMC-NLT incorporates multiple learning into a unified model such that hidden information can be extracted effectively from incomplete views. We conducted comprehensive experiments on five real-world datasets to validate the performance of IMC-NLT. The overall experimental results demonstrate that the proposed IMC-NLT performs better than several baseline methods, yielding stable and promising results.2. Collaborative fusion for incomplete multi-view data: our approach to address this issue is Incomplete Multi-view Co-Clustering by Sparse Low-Rank Representation (CCIM-SLR). The algorithm is based on sparse low-rank representation and subspace representation, in which jointly missing data is filled using data within a modality and related data from other modalities. To improve the stability of clustering results for multi-view data with different missing degrees, CCIM-SLR uses the Γ-norm model, which is an adjustable low-rank representation method. CCIM-SLR can alternate between learning the shared hidden view, visible view, and cluster partitions within a co-learning framework. An iterative algorithm with guaranteed convergence is used to optimize the proposed objective function. Compared with other baseline models, CCIM-SLR achieved the best performance in the comprehensive experiments on the five benchmark datasets, particularly on those with varying degrees of incompleteness.3. Enhancing the clustering robustness for incomplete multi-view data: we offer a fusion of graph convolution and information bottlenecks (Incomplete Multi-view Representation Learning Through Anchor Graph-based GCN and Information Bottleneck - IMRL-AGI). First, we introduce the information bottleneck theory to filter out the noise data with irrelevant details and retain only the most relevant feature items. Next, we integrate the graph structure information based on anchor points into the local graph information of the state fused into the shared information representation and the information representation learning process of the local specific view, a process that can balance the robustness of the learned features and improve the robustness. Finally, the model integrates multiple representations with the help of information bottlenecks, reducing the impact of redundant information in the data. Extensive experiments are conducted on several real-world datasets, and the results demonstrate the superiority of IMRL-AGI. Specifically, IMRL-AGI shows significant improvements in clustering and classification accuracy, even in the presence of high view missing rates (e.g. 10.23% and 24.1% respectively on the ORL dataset)
Goulart, José Henrique De Morais. "Estimation de modèles tensoriels structurés et récupération de tenseurs de rang faible." Thesis, Université Côte d'Azur (ComUE), 2016. http://www.theses.fr/2016AZUR4147/document.
Full textIn the first part of this thesis, we formulate two methods for computing a canonical polyadic decomposition having linearly structured matrix factors (such as, e.g., Toeplitz or banded factors): a general constrained alternating least squares (CALS) algorithm and an algebraic solution for the case where all factors are circulant. Exact and approximate versions of the former method are studied. The latter method relies on a multidimensional discrete-time Fourier transform of the target tensor, which leads to a system of homogeneous monomial equations whose resolution provides the desired circulant factors. Our simulations show that combining these approaches yields a statistically efficient estimator, which is also true for other combinations of CALS in scenarios involving non-circulant factors. The second part of the thesis concerns low-rank tensor recovery (LRTR) and, in particular, the tensor completion (TC) problem. We propose an efficient algorithm, called SeMPIHT, employing sequentially optimal modal projections as its hard thresholding operator. Then, a performance bound is derived under usual restricted isometry conditions, which however yield suboptimal sampling bounds. Yet, our simulations suggest SeMPIHT obeys optimal sampling bounds for Gaussian measurements. Step size selection and gradual rank increase heuristics are also elaborated in order to improve performance. We also devise an imputation scheme for TC based on soft thresholding of a Tucker model core and illustrate its utility in completing real-world road traffic data acquired by an intelligent transportation
Harmouch, Jouhayna. "Décomposition de petit rang, problèmes de complétion et applications : décomposition de matrices de Hankel et des tenseurs de rang faible." Thesis, Université Côte d'Azur (ComUE), 2018. http://www.theses.fr/2018AZUR4236/document.
Full textWe study the decomposition of a multivariate Hankel matrix as a sum of Hankel matrices of small rank in correlation with the decomposition of its symbol σ as a sum of polynomialexponential series. We present a new algorithm to compute the low rank decomposition of the Hankel operator and the decomposition of its symbol exploiting the properties of the associated Artinian Gorenstein quotient algebra . A basis of is computed from the Singular Value Decomposition of a sub-matrix of the Hankel matrix . The frequencies and the weights are deduced from the generalized eigenvectors of pencils of shifted sub-matrices of Explicit formula for the weights in terms of the eigenvectors avoid us to solve a Vandermonde system. This new method is a multivariate generalization of the so-called Pencil method for solving Pronytype decomposition problems. We analyse its numerical behaviour in the presence of noisy input moments, and describe a rescaling technique which improves the numerical quality of the reconstruction for frequencies of high amplitudes. We also present a new Newton iteration, which converges locally to the closest multivariate Hankel matrix of low rank and show its impact for correcting errors on input moments. We study the decomposition of a multi-symmetric tensor T as a sum of powers of product of linear forms in correlation with the decomposition of its dual as a weighted sum of evaluations. We use the properties of the associated Artinian Gorenstein Algebra to compute the decomposition of its dual which is defined via a formal power series τ. We use the low rank decomposition of the Hankel operator associated to the symbol τ into a sum of indecomposable operators of low rank. A basis of is chosen such that the multiplication by some variables is possible. We compute the sub-coordinates of the evaluation points and their weights using the eigen-structure of multiplication matrices. The new algorithm that we propose works for small rank. We give a theoretical generalized approach of the method in n dimensional space. We show a numerical example of the decomposition of a multi-linear tensor of rank 3 in 3 dimensional space. We show a numerical example of the decomposition of a multi-symmetric tensor of rank 3 in 3 dimensional space. We study the completion problem of the low rank Hankel matrix as a minimization problem. We use the relaxation of it as a minimization problem of the nuclear norm of Hankel matrix. We adapt the SVT algorithm to the case of Hankel matrix and we compute the linear operator which describes the constraints of the problem and its adjoint. We try to show the utility of the decomposition algorithm in some applications such that the LDA model and the ODF model
Castaing, Joséphine. "Méthodes PARAFAC pour la séparation de signaux." Cergy-Pontoise, 2006. http://biblioweb.u-cergy.fr/theses/06CERG0324.pdf.
Full textIn different applications, the observed signals can be stacked in a third-order tensor that can be decomposed in a sum of rank-one tensors. Such a decomposition is called PARAFAC. Our work presents a new method to estimate the parameters of the decomposition based on a simultaneous diagonalization and yields a new bound on the number of these parameters. We apply this method to CDMA signals, which have the PARAFAC structure. Moreover, we propose to combine PARAFAC structure and constant modulus constraint on the sources. We also show that it is possible to exploit the algebraic structure of the data to perform Independent Component Analysis in the underdetermined case. Finally, we study the rank of a random tensor, called generic rank, and we propose a technique to compute this rank in some particular cases
Lestandi, Lucas. "Approximations de rang faible et modèles d'ordre réduit appliqués à quelques problèmes de la mécanique des fluides." Thesis, Bordeaux, 2018. http://www.theses.fr/2018BORD0186/document.
Full textNumerical simulation has experienced tremendous improvements in the last decadesdriven by massive growth of computing power. Exascale computing has beenachieved this year and will allow solving ever more complex problems. But suchlarge systems produce colossal amounts of data which leads to its own difficulties.Moreover, many engineering problems such as multiphysics or optimisation andcontrol, require far more power that any computer architecture could achievewithin the current scientific computing paradigm. In this thesis, we proposeto shift the paradigm in order to break the curse of dimensionality byintroducing decomposition and building reduced order models (ROM) for complexfluid flows.This manuscript is organized into two parts. The first one proposes an extendedreview of data reduction techniques and intends to bridge between appliedmathematics community and the computational mechanics one. Thus, foundingbivariate separation is studied, including discussions on the equivalence ofproper orthogonal decomposition (POD, continuous framework) and singular valuedecomposition (SVD, discrete matrices). Then a wide review of tensor formats andtheir approximation is proposed. Such work has already been provided in theliterature but either on separate papers or into a purely applied mathematicsframework. Here, we offer to the data enthusiast scientist a comparison ofCanonical, Tucker, Hierarchical and Tensor train formats including theirapproximation algorithms. Their relative benefits are studied both theoreticallyand numerically thanks to the python library texttt{pydecomp} that wasdeveloped during this thesis. A careful analysis of the link between continuousand discrete methods is performed. Finally, we conclude that for mostapplications ST-HOSVD is best when the number of dimensions $d$ lower than fourand TT-SVD (or their POD equivalent) when $d$ grows larger.The second part is centered on a complex fluid dynamics flow, in particular thesingular lid driven cavity at high Reynolds number. This flow exhibits a seriesof Hopf bifurcation which are known to be hard to capture accurately which iswhy a detailed analysis was performed both with classical tools and POD. Oncethis flow has been characterized, emph{time-scaling}, a new ``physics based''interpolation ROM is presented on internal and external flows. This methodsgives encouraging results while excluding recent advanced developments in thearea such as EIM or Grassmann manifold interpolation
Rabusseau, Guillaume. "A tensor perspective on weighted automata, low-rank regression and algebraic mixtures." Thesis, Aix-Marseille, 2016. http://www.theses.fr/2016AIXM4062.
Full textThis thesis tackles several problems exploring connections between tensors and machine learning. In the first chapter, we propose an extension of the classical notion of recognizable function on strings and trees to graphs. We first show that the computations of weighted automata on strings and trees can be interpreted in a natural and unifying way using tensor networks, which naturally leads us to define a computational model on graphs: graph weighted models; we then study fundamental properties of this model and present preliminary learning results. The second chapter tackles a model reduction problem for weighted tree automata. We propose a principled approach to the following problem: given a weighted tree automaton with n states, how can we find an automaton with m
Luu, Thi Hieu. "Amélioration du modèle de sections efficaces dans le code de cœur COCAGNE de la chaîne de calculs d'EDF." Thesis, Paris 6, 2017. http://www.theses.fr/2017PA066120/document.
Full textIn order to optimize the operation of its nuclear power plants, the EDF's R&D department iscurrently developing a new calculation chain to simulate the nuclear reactors core with state of the art tools. These calculations require a large amount of physical data, especially the cross-sections. In the full core simulation, the number of cross-section values is of the order of several billions. These cross-sections can be represented as multivariate functions depending on several physical parameters. The determination of cross-sections is a long and complex calculation, we can therefore pre-compute them in some values of parameters (online calculations), then evaluate them at all desired points by an interpolation (online calculations). This process requires a model of cross-section reconstruction between the two steps. In order to perform a more faithful core simulation in the new EDF's chain, the cross-sections need to be better represented by taking into account new parameters. Moreover, the new chain must be able to calculate the reactor in more extensive situations than the current one. The multilinear interpolation is currently used to reconstruct cross-sections and to meet these goals. However, with this model, the number of points in its discretization increases exponentially as a function of the number of parameters, or significantly when adding points to one of the axes. Consequently, the number and time of online calculations as well as the storage size for this data become problematic. The goal of this thesis is therefore to find a new model in order to respond to the following requirements: (i)-(online) reduce the number of pre-calculations, (ii)-(online) reduce stored data size for the reconstruction and (iii)-(online) maintain (or improve) the accuracy obtained by multilinear interpolation. From a mathematical point of view, this problem involves approaching multivariate functions from their pre-calculated values. We based our research on the Tucker format - a low-rank tensor approximation in order to propose a new model called the Tucker decomposition . With this model, a multivariate function is approximated by a linear combination of tensor products of one-variate functions. These one-variate functions are constructed by a technique called higher-order singular values decomposition (a « matricization » combined with an extension of the Karhunen-Loeve decomposition). The so-called greedy algorithm is used to constitute the points related to the resolution of the coefficients in the combination of the Tucker decomposition. The results obtained show that our model satisfies the criteria required for the reduction of the data as well as the accuracy. With this model, we can eliminate a posteriori and a priori the coefficients in the Tucker decomposition in order to further reduce the data storage in online steps but without reducing significantly the accuracy
Diop, Mamadou. "Décomposition booléenne des tableaux multi-dimensionnels de données binaires : une approche par modèle de mélange post non-linéaire." Thesis, Université de Lorraine, 2018. http://www.theses.fr/2018LORR0222/document.
Full textThis work is dedicated to the study of boolean decompositions of binary multidimensional arrays using a post nonlinear mixture model. In the first part, we introduce a new approach for the boolean factorization of binary matrices (BFBM) based on a post nonlinear mixture model. Unlike the existing binary matrix factorization methods, the proposed method is equivalent to the boolean factorization model when the matrices are strictly binary and give thus more interpretable results in the case of correlated sources and lower rank matrix approximations compared to other state-of-the-art algorithms. A necessary and suffi-cient condition for the uniqueness of the BFBM is also provided. Two algorithms based on multiplicative update rules are proposed and tested in numerical simulations, as well as on a real dataset. The gener-alization of this approach to the case of binary multidimensional arrays (tensors) leads to the boolean factorisation of binary tensors (BFBT). The proof of the necessary and sufficient condition for the boolean decomposition of binary tensors is based on a notion of boolean independence of binary vectors. The multiplicative algorithm based on the post nonlinear mixture model is extended to the multidimensional case. We also propose a new algorithm based on an AO-ADMM (Alternating Optimization-ADMM) strategy. These algorithms are compared to state-of-the-art algorithms on simulated and on real data
Haberstich, Cécile. "Adaptive approximation of high-dimensional functions with tree tensor networks for Uncertainty Quantification." Thesis, Ecole centrale de Nantes, 2020. http://www.theses.fr/2020ECDN0045.
Full textUncertainty quantification problems for numerical models require a lot of simulations, often very computationally costly (in time and/or memory). This is why it is essential to build surrogate models that are cheaper to evaluate. In practice, the output of a numerical model is represented by a function, then the objective is to construct an approximation.The aim of this thesis is to construct a controlled approximation of a function while using as few evaluations as possible.In a first time, we propose a new method based on weighted least-squares to construct the approximation of a function onto a linear approximation space. We prove that the projection verifies a numerical stability property almost surely and a quasi-optimality property in expectation. In practice we observe that the sample size is closer to the dimension of the approximation space than with existing weighted least-squares methods.For high-dimensional approximation, and in order to exploit potential low-rank structures of functions, we consider the model class of functions in tree-based tensor formats. These formats admit a multilinear parametrization with parameters forming a tree network of low-order tensors and are therefore also called tree tensor networks. In this thesis we propose an algorithm for approximating functions in tree-based tensor formats. It consists in constructing a hierarchy of nested subspaces associated to the different levels of the tree. The construction of these subspaces relies on principal component analysis extended to multivariate functions and the new weighted least-squares method. To reduce the number of evaluations necessary to build the approximation with a certain precision, we propose adaptive strategies for the control of the discretization error, the tree selection, the control of the ranks and the estimation of the principal components
Papaix, Claire. "Mise en œuvre des instruments de politique publique allant dans le sens d’une mobilité bas carbone des personnes en milieu urbain." Thesis, Paris Est, 2015. http://www.theses.fr/2015PEST0059.
Full textThis PhD thesis deals with the reconciliation of the global challenge that is climate change and the local and sectoral solutions that need to be accurately designed to remedy to it the most efficiently, equitably and acceptably possible. More specifically, we investigate the conditions for a successful implementation of climate policy at the scale of the urban mobility of passengers
Book chapters on the topic "Tenseurs de bas rang"
"Chapitre 10 Tenseurs de rang 2." In Symétrie et propriétés physiques des cristaux, 193–212. EDP Sciences, 2020. http://dx.doi.org/10.1051/978-2-7598-0927-1-016.
Full text"Chapitre 10 Tenseurs de rang 2." In Symétrie et propriétés physiques des cristaux, 193–212. EDP Sciences, 2020. http://dx.doi.org/10.1051/978-2-7598-0927-1.c016.
Full textReports on the topic "Tenseurs de bas rang"
Boujija, Yacine, Marie Connolly, and Xavier St-Denis. Mobilité géographique et transmission intergénérationnelle du revenu au Québec. CIRANO, June 2023. http://dx.doi.org/10.54932/klji2908.
Full text