Seminar Details
2022-02-08 (14h) : Welcome Seminar
At Euler building (room a.002)
Organized by Mathematical Engineering
Section 1: Extension of the Performance Estimation framework through constraint interpolation.
Speaker :
Anne Rubbens (PhD UCLouvain/INMA)
Abstract :
Selecting parameters involved in an optimization algorithm is a major challenge often without satisfactory solution, and can have a dramatic impact on the algorithm performance. For instance, selecting parameters by optimizing performance bounds that are not exact may lead to misguided choices.Recently, an approach called Performance Estimation Problem (PEP) has been developed to automatically compute exact worst-case bounds on the performance of a wide class of optimization algorithms whose input belongs to a given class of functions, for instance convex functions.This project consists in extending the field of application of this approach to classes of functions for which no satisfactory PEP formulation exists yet. PEP formulations rely on necessary and sufficient interpolation conditions, ensuring the existence of a function of a given class interpolating a finite set of data. Hence, we will provide a novel approach to derive interpolation conditions for various classes of functions.
Section 2: Optimization of compositional functions
Speaker :
Bousselmi, Nizar
Abstract :
We consider functions with compositional structure, i.e., functions that can be expressed using one or several compositions of simple elementary component functions. These functions naturally appear in many practical problems. We would like to analyze the impact of the compositional structure of objective functions on the performance of the existing methods and to develop new methods exploiting this structure.
Section 3: Automatic quality control of weather and climate time series
Speaker :
Loucheur, Benoît
Abstract :
In Belgium, the Royal Meteorological Institute (RMI) is the national meteorological service that provide weather and climate services based on observations and scientific research. The RMI collects and archives meteorological observations in Belgium since the 19th century. Currently, air temperature is monitored in Belgium in about 30 synoptic automatic weather stations as well as in 110 manual climatological stations. All observations are routinely checked for errors, inconsistencies and missing values by the RMI staff. Misleading data are corrected and gaps are filled by estimations. This quality control tasks require a lot of human intervention. With the forthcoming deployment of low-cost weather stations and the subsequent increase in the volume of data to verify, the process of data quality control and completion should become as automated as much as possible. The aim of this project is to develop algorithmic tools to address this quality control problem in a fully automatic way.