se modifican conferencias y sesiones

data/conferencias.yml

@@ -81,25 +81,27 @@
       nombre: Mauricio Velasco
       afiliacion: Universidad de los Andes
       web: http://wwwprof.uniandes.edu.co/~mvelasco/Velasco.html
-  - titulo: TBC
-    abstract: ''      
+  - titulo: Pointed Hopf algebras over nilpotent groups
+    abstract: I will report on the ongoing project of classifying pointed Hopf algebras with finite Gelfand-Kirillov dimension.
     pdf: ''
     speaker:
       nombre: Nicolás Andruskiewitsch
       afiliacion: Universidad Nacional de Córdoba
       web: https://www.famaf.unc.edu.ar/~andrus/
-  - titulo: TBC 
-    abstract: ''
+  - titulo: Optimal adjustment sets in non-parametric causal graphical models 
+    abstract: Causal graphical models are statistical models represented by a directed acyclic graph in which each vertex stands for a random variable and a structural equation that generates it which is a function of its parents in the graph and an independent error.
+              I will start with a brief introduction of causal graphical models and of their use in the determination of identifiability and optimal estimation of the so-called average treatment effect (ATE) of static and personalized treatments in the presence of confounding variables.
+              I will then consider the problem of determining the best set of potential confounding variables at the stage of the design of a planned observational study aimed at assessing the population average causal effect of a point exposure personalized, i.e. dynamic, or static treatment. Given a tentative non-parametric graphical causal model, possibly including unobservable variables, the goal is to select the "best" set of observable covariates in the sense that it suffices to control for confounding under the model and it yields a non-parametric estimator of ATE with smallest variance. For studies without unobservables aimed at assessing the effect of a static point exposure we show that graphical rules recently derived for identifying optimal covariate adjustment sets in linear causal graphical models and treatment effects estimated via ordinary least squares also apply in the non-parametric setting. We further extend these results to personalized treatments. Moreover, we show that, in graphs with unobservable variables, but with at least one adjustment set fully observable, there exist adjustment sets that are optimal minimal (minimum), yielding non-parametric estimators with the smallest variance among those that control for observable adjustment sets that are minimal (of minimum cardinality). In addition, although a globally optimal adjustment set among observable adjustment sets does not always exist, we provide a sufficient condition for its existence. We provide polynomial time algorithms to compute the observable globally optimal (when it exists), optimal minimal, and optimal minimum adjustment sets. This is joint work with Ezequiel Smucler and Facundo Sapienza.
     pdf: ''
     speaker:
       nombre: Andrea Rotnizky
-      afiliacion: School of Public Health Harvard T.H. CHAN
+      afiliacion: Universidad di Tella, Buenos Aires
       web: https://www.hsph.harvard.edu/andrea-rotnitzky/
-  - titulo: TBA 
+  - titulo: Inviscid dissipation and turbulence 
     abstract: ''
     pdf: ''
     speaker:
-      nombre: Helena Nussensveig
+      nombre: Helena Nussenszveig Lopes
       afiliacion: Universidad Federal de Rio de Janeiro
       web: http://www.im.ufrj.br/hlopes/
   - titulo: Unique Continuation for some Nonlinear Dispersive Models

data/sesiones.yml

@@ -177,12 +177,6 @@
     mail: pamster@dm.uba.ar	
   - nombre: Gonzalo Robledo
     mail: grobledo@uchile.cl
-- titulo: Educación matemática
-  organizadores:
-  - nombre: Elizabeth Montoya Delgadillo
-    mail: elizabeth.montoya@pucv.cl	
-  - nombre: Miguel Ribeiro
-    mail: cmribas78@gmail.com
 - titulo: Problemas Variacionales y Ecuaciones Diferenciales Parciales
   organizadores:
   - nombre: Judith Campos Cordero
@@ -213,7 +207,7 @@
     mail: gregorio.malajovich@gmail.com	
   - nombre: Diego Armentano
     mail: diego@cmat.edu.uy
-- titulo: Análisis Wavelete y aplicaciones
+- titulo: Análisis wavelets y aplicaciones
   organizadores:
   - nombre: Victoria Vampa
     mail: victoriavampa@gmail.com	
@@ -232,9 +226,7 @@
   - nombre: Noé Bárcenas
     mail: barcenas@matmor.unam.mx	
   - nombre: Eugenia Ellis
-    mail: eellis@fing.edu.uy	
-  - nombre: Emanuel Rodríguez Cirone
-    mail: ercirone@dm.uba.ar
+    mail: eellis@fing.edu.uy	  
 - titulo: Stochastic analysis and stochastic processes
   organizadores:
   - nombre: Paavo Salminen