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pro vyhledávání: '"Barthelmé A"'
We study (topological) pseudo-Anosov flows from the perspective of the associated group actions on their orbit spaces and boundary at infinity. We extend the definition of Anosov-like action from [BFM22] from the transitive to the general non-transit
Externí odkaz:
http://arxiv.org/abs/2411.03586
Node regression consists in predicting the value of a graph label at a node, given observations at the other nodes. To gain some insight into the performance of various estimators for this task, we perform a theoretical study in a context where the g
Externí odkaz:
http://arxiv.org/abs/2410.21987
Autor:
Usevich, Konstantin, Barthelme, Simon
Computing the eigenvectors and eigenvalues of a perturbed matrix can be remarkably difficult when the unperturbed matrix has repeated eigenvalues. In this work we show how the limiting eigenvectors and eigenvalues of a symmetric matrix $K(\varepsilon
Externí odkaz:
http://arxiv.org/abs/2407.17047
Motivated by problems in the study of Anosov and pseudo-Anosov flows on 3-manifolds, we characterize when a pair $(L^+, L^-)$ of subsets of transverse laminations of the circle can be completed to a pair of transverse foliations of the plane or, sepa
Externí odkaz:
http://arxiv.org/abs/2406.18917
Random diffusions are a popular tool in Monte-Carlo estimations, with well established algorithms such as Walk-on-Spheres (WoS) going back several decades. In this work, we introduce diffusion estimators for the problems of angular synchronization an
Externí odkaz:
http://arxiv.org/abs/2403.19300
In [Orbit equivalences of pseudo-Anosov flows, arXiv:2211.10505], it was proved that transitive pseudo-Anosov flows on any closed 3-manifold are determined up to orbit equivalence by the set of free homotopy classes represented by periodic orbits, pr
Externí odkaz:
http://arxiv.org/abs/2308.02098
We prove a classification theorem for transitive Anosov and pseudo-Anosov flows on closed 3-manifolds, up to orbit equivalence. In many cases, flows on a 3-manifold $M$ are completely determined by the set of free homotopy classes of their (unoriente
Externí odkaz:
http://arxiv.org/abs/2211.10505
Discrete Determinantal Point Processes (DPPs) have a wide array of potential applications for subsampling datasets. They are however held back in some cases by the high cost of sampling. In the worst-case scenario, the sampling cost scales as O(n^3)
Externí odkaz:
http://arxiv.org/abs/2210.17358
Autor:
Jaquard, Hugo, Fanuel, Michaël, Amblard, Pierre-Olivier, Bardenet, Rémi, Barthelmé, Simon, Tremblay, Nicolas
We introduce new smoothing estimators for complex signals on graphs, based on a recently studied Determinantal Point Process (DPP). These estimators are built from subsets of edges and nodes drawn according to this DPP, making up trees and unicycles,
Externí odkaz:
http://arxiv.org/abs/2210.08014
Publikováno v:
GRETSI 2022 - XXVIII{\`e}me Colloque Francophone de Traitement du Signal et des Images, Sep 2022, Nancy, France
The trace $\tr(q(\ma{L} + q\ma{I})^{-1})$, where $\ma{L}$ is a symmetric diagonally dominant matrix, is the quantity of interest in some machine learning problems. However, its direct computation is impractical if the matrix size is large. State-of-t
Externí odkaz:
http://arxiv.org/abs/2206.07421