CORDIS - Forschungsergebnisse der EU
CORDIS

Big Data Challenges for Mathematics

Leistungen

Ready-to-use stochastic geometric models

At the completion of WP3, we will have ready-to-use theoretical models implemented into computational codes, and validated with data from existing or new experiments taken from scans of real human faces.

Outreach activities I

Participation of the ESRs to outreach activities for the first reporting period: 1. Preparation of sessions/labs to the national “Night of researcher” events 2. Participation of the ESRs to scientific or technological fairs

Outreach activities II

Participation of the ESRs to outreach activities for the second reporting period: 1. Preparation of sessions/labs to the national “Night of researcher” events2. Participation of the ESRs to scientific or technological fairs

Final dissemination workshop

Final workshop on future valorisation of the results, industrial knowledge transfer and dissemination The deliverable will include the agenda, the presentations, the conclusions, photos, etc.

Report on Statistical methods for Imbalanced classification – Version I

The WPL will submit an on-going work report to the SB covering in detail the WP progress up to month 24. The goals of the report are to summarize, disseminate, and re-evaluate the WP strategy, if needed.

Final report on stochastic geometric space-time models

The WP leader will elaborate a report that will be submitted to the SB This report will provide a detailed summary of the implementation of the whole WP It will serve to measure the rate of success of the investigation that has been developed and to evaluate the scientific achievements that have been reached

Report on Statistical methods for Imbalanced classification - Version II

The WPL will submit a report to the SB covering in detail the WP progress The goal of the report is to review the scientific achievements within the WP

Potential inputs for policy feedback

Report with recommendations to EU to enhance European competitiveness in the fields of the EU policy priorities involved in BIGMATH in particular Big Data

Report on distributed and non-convex optimization—Version II

the WP leader will elaborate the final version of a report that will be submitted to the SB This report will provide a detailed summary of the implementation of the whole WP It will serve to measure the degree of success of the investigation that has been developed and to evaluate the scientific achievements that have been reached

Report on distributed and non-convex optimization—Version I

the WP leader will elaborate a preliminary version of a report that will be submitted to the SB. This report will provide a detailed summary of the implementation of the whole WP up to month 24. It will serve to measure the degree of success of the investigation that has been developed so far, and to adjust the strategy for the subsequent project period, as needed.

Supervisory Board of the network

Document establishing the Supervisory Board and defining the way of working

Progress report of WP3

Progress report on the scientific activities of WP3

Report on large-scale linear algebra, model reduction and features extraction —Version II

the WP leader will elaborate a final report that will be submitted to the SB This report will provide a detailed summary of the implementation of the whole WP It will serve as a review and give a summary of the scientific achievements that have been reached

Report on large-scale linear algebra, model reduction and features extraction—Version I

the WP leader will elaborate a preliminary report that will be submitted to the SB. This report will provide a detailed summary of the implementation of the whole WP up to month 24. It will serve to summarize and disseminate the progress so far, and to adjust the strategy if needed.

BIGMATH blog and socials

opening of accounts on main social media and of a blog related with the project, managed by the ESRs

BIGMATH website

web site of the project

Veröffentlichungen

A Hybrid DEIM and Leverage Scores Based Method for CUR Index Selection

Autoren: Gidisu P.Y., Hochstenbach M.E.
Veröffentlicht in: Progress in Industrial Mathematics at ECMI 2021, Ausgabe vol 39, 2022, Seite(n) 147-153, ISBN 978-3-031-11818-0
Herausgeber: Springer
DOI: 10.1007/978-3-031-11818-0_20

Emotion pattern detection on facial videos using functional statistics

Autoren: Ji, Rongjiao; Micheletti, Alessandra; Jerinkic, Natasa Krklec; Desnica, Zoranka
Veröffentlicht in: Book of short papers - SIS 2021, 2021, Seite(n) 789-794, ISBN 9788891927361
Herausgeber: Pearson

Distributed fixed point method for solving systems of linear algebraic equations

Autoren: Dušan Jakovetić, Nataša Krejić, Nataša Krklec Jerinkić, Greta Malaspina, Alessandra Micheletti
Veröffentlicht in: Automatica, Ausgabe 134, 2021, Seite(n) 109924, ISSN 0005-1098
Herausgeber: Pergamon Press Ltd.
DOI: 10.1016/j.automatica.2021.109924

Understanding heterogeneity of investor sentiment on social media: A structural topic modeling approach

Autoren: Rongjiao Ji, Qiwei Han
Veröffentlicht in: Frontiers in Artificial Intelligence, Ausgabe 26248212, 2022, ISSN 2624-8212
Herausgeber: Frontiers
DOI: 10.3389/frai.2022.884699

From Noisy Point Clouds to Complete Ear Shapes: Unsupervised Pipeline

Autoren: Filipa Valdeira, Ricardo Ferreira, Alessandra Micheletti, Claudia Soares
Veröffentlicht in: IEEE Access, Ausgabe 9, 2021, Seite(n) 127720-127734, ISSN 2169-3536
Herausgeber: Institute of Electrical and Electronics Engineers Inc.
DOI: 10.1109/access.2021.3111811

A Generalized CUR decomposition for matrix pairs

Autoren: Perfect Y. Gidisu; Michiel E. Hochstenbach
Veröffentlicht in: SIAM Journal on Mathematics of Data Science, Ausgabe 4, 2022, Seite(n) 386-409, ISSN 2577-0187
Herausgeber: SIAM Publications LIbrary
DOI: 10.1137/21m1432119

Functional statistics for human emotion detection

Autoren: Rongjiao Ji, Alessandra Micheletti, Natasa Krklec Jerinkic, Zoranka Desnica
Veröffentlicht in: Mathematics with industry: driving innovation. Annual report., Ausgabe 2020, 2021, Seite(n) 26-30, ISSN 2616-7875
Herausgeber: European Consortium for Mathematics in Industry

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