Noticias en español
Seminars appear in decreasing order in relation to date. To find an activity of your interest just go down on the list. Normally seminars are given in English. If not, they will be marked as Spanish Only.
Morse theory for the action functional and a Poincare-Birkhoff theorem for flows
ABSTRACT: The goal of this talk is twofold. Firstly I would like to explain how pseudo-holomorphic curves can be used to study Morse theory of the action functional from classical mechanics. Then I will move to applications, focusing on a generalization of the Poincare-Birkhoff theorem for Reeb flows on the three-sphere.
Norm and pointwise averages of multiple ergodic averages and applications
ABSTRACT: Via the study of multiple ergodic averages for a single transformation, Furstenberg, in 1977, was able to provide an ergodic theoretical proof of Szemerédi’s theorem, i.e., every subset of natural numbers of positive upper density contains arbitrarily long arithmetic progressions. We will present some recent developments in the area for more general averages, e.g., for multiple commuting transformations with iterates along specific classes of integer valued sequences. We will also get numerous applications of the...
Variables No-Académicas que Explican la Brecha de Género en Matemática: Datos de Chile
Resumen: En Chile existe una de las mayores brechas de género -a nivel mundial- en los aprendizajes de matemática, la que se agudiza en los niveles socioeconómicos más bajos. La literatura explica este fenómeno en base a factores culturales, como son las llamadas variables no-académicas, como estereotipos sobre matemática y género y el autoconcepto matemático. De esta forma, la evidencia internacional muestra que los niños y niñas desarrollan sus habilidades matemáticas influenciados por sus propias creencias y a las de los adultos más...
Scalable P-wave passive seismic topography
Abstract: The goal of this work is to simultaneously reconstruct the location-dependent velocity field of seismic P-waves in an underground mine, and the unknown seismic sources during a given period, or dynamically over time, by using only registered data of passively generated P-waves (in particular, not relying on calibration shots as is usually the case). To that end, we develop a two-step algorithm based on Bayesian modeling and on the use, to our knowledge for the first time in geostatistics applications, of a stochastic gradient...
About a problem on real time scheduling and control
Abstract: Certain control computations require to be co-scheduled, each of which is allowed to be skipped occasionally. This may be modeled as periodic tasks with the correctness requirement that for each one, the fraction of jobs that complete execution should be at least some specified value between zero and one. I will show you two different real time scheduling models to formalize the problem, and derive approximation algorithms. Time permitting, I would also like to discuss about the model and solution strategies, and what other variants...
Periodic Homogenization for Nonlocal Hamilton-Jacobi Equations at a Critical Diffusive Regime.
Abstract. In this talk, I will report periodic homogenization results for integro-differential Hamilton-Jacobi equations in which the nonlocal elliptic operator have “order” one. This makes the nonlocal operator to have the same scaling property of the gradient, which can be understood as a critical regime among the diffusion and the transport terms. This is a joint work with Adina Ciomaga (Paris Diderot University, Paris) and Daria Ghilli (Karl-Franzens-Universität Graz, Austria).
“ Dame control absolute sobre cada….”
Abstract: Como la letra de la canción de Leonard Cohen busco controlar pero no almas, sino ecuaciones. En esta charla presentaremos una visión panorámica de lo que es el control de ecuaciones parciales.
“Deep Variational Transfer: Transfer Learning through Semi-supervised Deep Generative Models”
Abstract: “In real-world applications, it is expensive and time-consuming to obtain labeled examples. In such cases, knowledge transfer from related domains, where labels are abundant, could greatly reduce the need for extensive labeling efforts. In this scenario, transfer and multi-task learning come in hand. In this paper, we propose Deep Variational Transfer (DVT), a variational autoencoder that transfers knowledge across domains using a shared latent Gaussian mixture model. More in details, we align all supervised examples of the...
