Séminaire au DIC: «Machine learning for stochastic optimization» par Janosh Ortmann
Vous êtes tous cordialement invité à assister au 2e séminaire au DIC, session hiver 2022, en partenariat avec l'ISC et le CRIA.
Janosh ORTMANN – 27 janvier 2022 à 10h30
Titre : Machine learning for stochastic optimization
In this talk, I will discuss several applications of machine learning in stochastic optimization, transport planning and humanitarian and healthcare logistics.In stochastic programming, scenarios are used to approximate the distributions of the unknown parameters and formulate and solve multi-stage stochastic optimization models. However, optimizing with respect to each scenario is computationally costly and it is often difficult to see how a change in assumptions impacts the solution. By considering the scenarios as data themselves and then applying unsupervised clustering methods to this data set we can obtain new insights into the underlying optimization problem. I will show how this leads to new upper and lower bounds, but also to deeper insights in applications such as humanitarian logistics and the planning of healthcare distribution networks. If time permits, I will also discuss how reinforcement learning can allow decision makers obtain new approximatively optimal solutions.
Janosh ORTMANN is an associate professor in Data Science and Business Intelligence at UQAM and a member of the Centre de Recherches Mathématiques (CRM) and the Group for Research in Decision Analysis (GERAD). He holds a PhD in mathematics from Warwick University and has completed postdoctoral fellowships at the University of Toronto, Université de Montréal and Concordia University. His main research interest lies in the analysis of decision making under uncertainty, particularly using techniques from machine learning, probability theory and operations research. Currently, he is working on applications such as the design of transport networks, humanitarian logistics and personalized medicine.
S.V.P. Vous connecter au moins 10 à 15 minutes avant l'heure et inscrire votre nom complet pour aider à vous admettre au séminaire.
La participation à micro et caméra ouverts est grandement appréciée lors de la période des questions.
Lien Zoom de la rencontre : https://uqam.zoom.us/j/85407268175