Archive for Florida
snapshot from UF campus
Posted in pictures, Running, Travel, University life with tags Challis Lecture, Florida, Gainesville, University of Florida, USA on November 15, 2014 by xi'an
back in Gainesville (FL)
Posted in pictures, Running, Statistics, Travel, University life, Wines with tags ABC, Challis Lecture, finite mixtures, Florida, Gainesville, George Casella, random forests, seminar, University of Florida on November 12, 2014 by xi'an
Today, I am flying to Gainesville, Florida, for the rest of the week, to give a couple of lectures. More precisely, I have actually been nominated the 2014 Challis lecturer by the Department of Statistics there, following an impressive series of top statisticians (most of them close friends, is there a correlation there?!). I am quite excited to meet again with old friends and to be back at George’s University, if only for a little less than three days. (There is a certain trend in those Fall trips as I have been going for a few days and two talks to the USA or Canada for the past three Falls: to Ames and Chicago in 2012, to Pittsburgh (CMU) and Toronto in 2013…)
métro static
Posted in pictures, Running with tags Badwater Ultramarathon, Florida, Marathon FL, métro, métro static, Paris, sea, sunset on September 27, 2014 by xi'an
“Mon premier marathon je le fais en courant.” [I will do my first marathon running.]
Sean Meyn in Paris
Posted in Books, Statistics, Travel with tags dynamic programming, Florida, Gainesville, Markov chains, Paris, reinforcement learning, Sean Meyn, seminar on November 23, 2013 by xi'anMy friend Sean Meyn (from the University of Florida, Gainesville) will give a talk in Paris next week (and I will be away in Coventry at the time…). Here are the details:
Mardi 26 novembre 2013 à 14h00
Salle de Conseil, 4ème étage (LINCS) 23 AVENUE D’ITALIE 75013 PARISTitre de l’exposé : Feature Selection for Neuro-Dynamic Programming
Neuro-Dynamic Programming encompasses techniques from both reinforcement learning and approximate dynamic programming. Feature selection refers to the choice of basis that defines the function class that is required in the application of these techniques. This talk reviews two popular approaches to neuro-dynamic programming, TD-learning and Q-learning. The main goal of this work is to demonstrate how insight from idealized models can be used as a guide for feature selection for these algorithms. Several approaches are surveyed, including fluid and diffusion models, and the application of idealized models arising from mean-field game approximations. The theory is illustrated with several examples.
Florida tree
Posted in pictures, Running, Travel, University life with tags Florida, Gainesville, morning light, Spanish moss, trees on January 21, 2013 by xi'an
