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Théorie de la complexité (informatique théorique)

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Informatique théorique
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Publications associées (27)

Page 2 sur 2

Special issue on computer graphics international 2022 part 1

Daniel Thalmann

WILEY2022

Learning Bayesian Networks in the Presence of Structural Side Information

Negar Kiyavash, Seyed Jalal Etesami, Ehsan Mokhtarian, Sina Akbari, Fateme Jamshidi

We study the problem of learning a Bayesian network (BN) of a set of variables when structural side information about the system is available. It is well known that learning the structure of a general BN is both computationally and statistically challengin ...

ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE2022

Analytical Computation of Power Grids’ Sensitivity Coefficients with Voltage-Dependent Injections

Mario Paolone, Sherif Alaa Salaheldin Fahmy

With the increasing need of real-time regulation in power systems, grid-aware-control-frameworks are relying more often on sensitivity coefficients (SCs) to formulate and efficiently solve optimal control problems. As known, SCs are the derivatives of cont ...

IEEE2021

Adaptive Laser Welding Control: A Reinforcement Learning Approach

Giulio Masinelli, Silvio Zanoli

Despite extensive research efforts in the field of laser welding, the imperfect repeatability of the weld quality still represents an open topic. Indeed, the inherent complexity of the underlying physical phenomena prevents the implementation of an effecti ...

2020

Computational studies on Escherichia coli metabolism : from constitutive bricks to large-scale behaviour

Stefano Andreozzi

Metabolic Engineering is fostered by an increasing effort and progress in the collection of large and accurate 'omics' datasets. The abundance of available measurements and advances in measurement techniques only alleviate to a certain extent the uncertai ...

EPFL2015

Graph-based classification of multiple observation sets

Pascal Frossard, Effrosyni Kokiopoulou

We consider the problem of classification of multiple observations of the same object, possibly under different transformations. We view this problem as a special case of semi-supervised learning where all unlabelled examples belong to the same unknown cla ...

Elsevier2010

A Tighter Analysis of Work Stealing

Nicolas Gabriel Gast

Classical list scheduling is a very popular and efficient technique for scheduling jobs in parallel platforms. However, with the increasing number of processors, the cost for managing a single centralized list becomes prohibitive. The objective of this wor ...

Springer Berlin Heidelberg2010