Study on the influence of diversity and quality in entropy based collaborative clustering

J Sublime, G Cabanes, B Matei - Entropy, 2019 - mdpi.com
The aim of collaborative clustering is to enhance the performances of clustering algorithms
by enabling them to work together and exchange their information to tackle difficult data sets …

Grid-based approach to determining parameters of the DBSCAN algorithm

A Starczewski, A Cader - Artificial Intelligence and Soft Computing: 19th …, 2020 - Springer
Clustering is a very important technique used in many fields in order to deal with large
datasets. In clustering algorithms, one of the most popular approaches is based on an …

Contributions to modern unsupervised learning: Case studies of multi-view clustering and unsupervised Deep Learning

J Sublime - 2021 - hal.science
This document is the manuscript presented in order to obtain the" Habilitation à Diriger des
Recherches" of Sorbonne University (France), prepared at ISEP Engineering School where I …

A novel explainable recommender for investment managers

T Rutkowski, R Nielek, D Rutkowska… - … Conference on Artificial …, 2020 - Springer
This paper presents a novel recommendation system for investment managers using real
data from asset management companies. The recommender can be viewed as a fuzzy …

Learning from Data and Learners

Y Foucade - 2022 - theses.hal.science
This thesis focuses on collaborative learning. This machine learning paradigm is one of the
many methods that have emerged in recent years in an attempt to efficiently mine the …

[PDF][PDF] Ecole doctorale: CY CERGY PARIS UNIVERSITE

N Grozavu, F SURMA - 2022 - sciences-patrimoine.org
Les besoins identifiés par la commission EU sur la question de l'impact du changement
climatique sur le patrimoine se focalisent sur le développement de plan d'exploitation des …

[PDF][PDF] Thesis subject Proposal

N Grozavu, LI Xiaoli - etis-lab.fr
In recent years, the in the Artificial Intelligence (AI) community, a lot of research and
applicative works have appeared dealing with the learning of neural networks architectures …

[PDF][PDF] Projet ANR (2020-2024) Hérelles: un cadre collaboratif uni é pour l'analyse interactive de données temporelles

P Gançarski, A Cornuejols, B Cremilleux, TBH Dao… - 1024.societe-informatique-de-france …
Face à la surabondance des données temporelles arrivant de façon quasi-continue, mais
aussi à leur complexité et à celle des phénomènes étudiés, définir les informations …

Gas Turbine Fault Detection Using a Self-Organising Map

KH Hui, CS Ooi, MH Lim, MD Yusoff… - Vibration Engineering for …, 2021 - Springer
Turbomachinery condition monitoring and fault detection in the Malaysian oil and gas
industry is currently done by monitoring the parameters of the equipment, such as a gas …