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Ph.D de

Ph.D
Group : Networking & Stochastic and Combinatorial Optimization

Chance Constrained Problem and Its Applications

Starts on 01/09/2016
Advisor : LISSER, Abdel

Funding : Autre financement à préciser
Affiliation : Université Paris-Saclay
Laboratory : LRI - ParSys

Defended on 17/06/2019, committee :
M. Yacine CHITOUR CentraleSupelec

Mme Francesca MAGGIONI University of Bergamo Via dei Caniana 2

Mme Janny LEUNG Chinese University of Hong Kong (Shenzhen)

M. Alexandre CAMINADA Université de Nice

M. Mounir HADDOU INSA Rennes

M. Abdel LISSER Université Paris-Sud

M. Zhiping CHEN Xi'an Jiaotong University

M. Vikas Vikram SINGH Department of Mathematics, IIT Delhi

Research activities :

Abstract :
Uncertainty is a natural property of complex systems. The target of optimization under uncertainty is to provide profitable and reliable decisions for systems with such uncertainties. Chance constrained optimization is a natural and widely used approach for the formulation of optimization problems under uncertainty.
In this talk, we will systematically investigate chance constrained problems from the following perspectives:
• Stochastic geometric program with rectangular constraints,
• Bounds for chance constrained problems,
• Distributionally robust chance constrained problem based on mixture model,
• Stochastic non-cooperative game with stochastic strategy constraints.

Ph.D. dissertations & Faculty habilitations
MICRO VISUALIZATIONS: DESIGN AND ANALYSIS OF VISUALIZATIONS FOR SMALL DISPLAY SPACES
The topic of this habilitation is the study of very small data visualizations, micro visualizations, in display contexts that can only dedicate minimal rendering space for data representations. For several years, together with my collaborators, I have been studying human perception, interaction, and analysis with micro visualizations in multiple contexts. In this document I bring together three of my research streams related to micro visualizations: data glyphs, where my joint research focused on studying the perception of small-multiple micro visualizations, word-scale visualizations, where my joint research focused on small visualizations embedded in text-documents, and small mobile data visualizations for smartwatches or fitness trackers. I consider these types of small visualizations together under the umbrella term ``micro visualizations.'' Micro visualizations are useful in multiple visualization contexts and I have been working towards a better understanding of the complexities involved in designing and using micro visualizations. Here, I define the term micro visualization, summarize my own and other past research and design guidelines and outline several design spaces for different types of micro visualizations based on some of the work I was involved in since my PhD.

A NEW GENERATION OF GRAPH NEURAL NETWORKS TO TACKLE AMORPHOUS MATERIALS


SPOTTING NEURAL NETWORK BOTTLENECKS AND FIXING THEM BY ARCHITECTURE GROWTH