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.
Approximating Vector Scheduling
Abstract: In this talk we will consider the Vector Scheduling problem, a natural generalization of the classical makespan minimization problem to multiple resources. Here, we are given n jobs, represented as d-dimensional vectors in [0,1]^d, and m identical machines, and the goal is to assign the jobs to machines such that the maximum load of each machine over all the coordinates is at most 1. For fixed d, the problem admits an approximation scheme, and the best known running time is n^{f(epsilon,d)}, where f(epsilon,d) = (1/epsilon)^{Õ(d)},...
On regularization/convexification of functionals including an l2-misfit term
Abstract: A common technique for solving ill-posed inverse problems is to include some sparsity/low-rank constraint, and pose it as a convex optimization problem, as is done e.g. in compressive sensing. The corresponding functional to be minimized often includes an l2 data fidelity term plus a convex term forcing sparsity. However, for many applications a non-convex term would be more suitable, although this is usually discarded since it leads to issues with algorithm convergence, local minima etc. I will introduce a new transform...
Markov Decision Processes with long duration
Abstract: In a Markov Decision Process (MDP), at each stage, knowing the current state, the decision-maker chooses an action, and receives a reward depending on the current state of the world. Then a new state is randomly drawn from a distribution depending on the action and on the past state. Many optimal payoffs concepts have been introduced to analyze the strategic aspects of MDPs with long duration: asymptotic value, uniform value, liminf average payoff criterion… We provide sufficient conditions under which these concepts coincide, and...
Canonical Supermartingle Couplings
ABSTRACT: Two probability distributions in second stochastic order can be coupled by a supermartingale, and in fact by many. Is there a canonical choice? We construct and investigate two couplings which arise as optimizers for constrained Monge-Kantorovich optimal transport problems where only supermartingales are allowed as transports. Much like the Hoeffding-Frechet coupling of classical transport and its symmetric counterpart, the Antitone coupling, these can be characterized by order-theoretic minimality properties, as simultaneous...
Local rules for planar tilings
ABSTRACT: The cut and project method is one of the prominent method to define quasiperiodic tilings. In order to model quasicrystals, where energetic interactions are only short range, it is important to know which of these tilings can be characterized by local configurations (in dynamical terms: which of these tiling spaces are of finite type or sofic). In this talk we shall review known results, in particular those obtained these last years with Nicolas Bedaride and Mathieu Sablik.
Dynamics of strongly interacting unstable two-solitons for generalized Korteweg-de Vries equations.
Abstract. Many evolution PDEs admit special solutions, called solitons, whose shape does not change in time. A multi-soliton is a solution which is close to a superposition of a finite number K of solitons placed at a large distance from each other. I am interested in describing multi-soliton dynamics for generalized Korteweg-de Vries equations. I will present a general method of formally predicting the time evolution of the centers and velocities of each soliton. Then I will discuss in detail the case K = 2, in particular in the...
CURTIS-HEDLUND-LYNDON THEOREM FOR ULTRAGRAPH SHIFT SPACES
ABSTRACT: In this work we characterize the class of continuous shift commuting maps between ultragraph shift spaces, proving a Curtis-Hedlund-Lyndon type theorem. Then we use it to characterize continuous, shift commuting, length preserving maps in terms of generalized sliding block codes. This is a joint work with Prof. Daniel Gon\c{c}alves (UFSC, Brazil)
Optimal transport and applications to Data Science
Abstract: Optimal transport (OT) provides rich representations of the discrepancy between probability measures supported on geometric spaces. Recently, thanks to the development of computational techniques, OT has been used to address problems involving massive datasets, as an alternative to usual KL-divergence based approaches. In this talk I will introduce the OT problem and comment on its elementary duality properties. Then, I will present the entropy regularized problem and its (fast) solution via Sinkhorn iterations. Finally, I will...
Projected solutions of quasi-variational inequalities with application to bidding process in electricity market
Abstract: Quasi-variational inequalities provide perfect tools to reformulate Generalized Nash Equilibrium Probem (GNEP), the latter being a good model to describe the day-ahead electricity markets. Our aim in this talk is to illustrate how some recent advances in the theory of quasi-variational inequalities can influence the modeling of electricity market. Talk based on: – D. Aussel, A. Sultana & V. Vetrivel, On the existence of projected solutions of quasi-variational inequalities and generalized Nash...
Physics-based Models for Uncertainty Quantification in Chemical Kinetics
Abstract: Prediction is a core element of science and engineering. Sophisticated mathematical models exist to make predictions in a variety of physical contexts including materials science, fluid mechanics, and solid mechanics. Most of these models do not have known analytical solutions. Moreover, they are generally difficult to solve numerically. In order to perform numerically tractable computations, researchers often try to develop reduced models that account for the essential physics while doing away with the complexity of the full...
