Summer School on Machine Learning and Big Data with Quantum Computing (SMBQ 2020)
Porto, Portugal, September 7-8, 2020
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Machine Learning (ML) is an Artificial Intelligence (AI) branch, that focuses on developing algorithms to teach how computers learn from data to make decisions or predictions. Deep Learning (DL) is part of a broader family of ML algorithms, that is based on artificial neural networks. Arguably, DL techniques demand for big amounts of data and, as such, they require huge computational resources and advanced processing techniques.
Cloud Computing is a well-known alternative to deal with big amounts of data, since its elasticity allows for an efficient scalability of huge computational resources, such as, data storage and processing power. On the other hand, Quantum Computing is an advanced processing technique, that uses the fundamentals of quantum mechanics to accelerate the process of solving highly complex problems.
SMBQ 2020 addresses the current trends in AI and in the computational techniques that deal with big data demands, together with, a powerful processing technique that will shape the future of computation.
During 2 days, from 7-8 September 2020, we will introduce concepts, discuss the current trends and provide direct practical experience in hands-on lessons.
For more information visit: smbq2020.dcc.fc.up.pt/
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Registration:
Attendance is free, but it is required that participants register in advance by filling a form until 15 August, 2020. Prior to the event, information regarding the access of the live sessions will be sent to all registrants via email.
The number of participants is limited, thus the registration process closes once the limit is reached. For any further information, please send a message to SMBQ2020.

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Contact Persons:
Carlos Ferreira, Polytechnic Institute of Porto, LIAAD – INESC TEC, E-mail: cgf@isep.ipp.pt Miguel Areias, University of Porto, CRACS – INESC TEC, E-mail: miguel-areias@dcc.fc.up.pt
Carlos Ferreira
ISEP | Instituto Superior de Engenharia do Porto Rua Dr. António Bernardino de Almeida, 431 4249-015 Porto – PORTUGAL tel. +351 228 340 500 | fax +351 228 321 159 mail@isep.ipp.pt | www.isep.ipp.pt

Call for Papers
SoGood 2020 – 5th Workshop on Data Science for Social Good Affiliated with ECML-PKDD 2020, 14-18 September 2020,https://ecmlpkdd2020.net/
Workshop site:https://sites.google.com/view/ecmlpkddsogood2020/
This is the fifth edition of the workshop; the previous workshops were held jointly with ECML-PKDD 2016, 2017, 2018 and 2019
The possibilities of Data Science for contributing to social, common, or public good are often not sufficiently perceived by the public at large. Data Science applications are already helping in serving people at the bottom of the economic pyramid, aiding people with special needs, helping international cooperation, and dealing with environmental problems, disasters, and climate change. In regular conferences and journals, papers on these topics are often scattered among sessions with names that hide their common nature (such as “Social networks”, “Predictive models” or the catch-all term “Applications”). Additionally, such forums tend to have a strong bias for papers that are novel in the strictly technical sense (new algorithms, new kinds of data analysis, new technologies) rather than novel in terms of social impact of the application.
This workshop aims to attract papers presenting applications of Data Science for Social Good (which may, or may not require new methods), or applications that take into account social aspects of Data Science methods and techniques. There are numerous application domains, a non-exclusive list includes:
* Government transparency and IT against corruption * Public safety and disaster relief * Public policies in epidemic growth and related issues * Access to food, water and utilities * Efficiency and sustainability * Data journalism * Economic, social and personal development * Transportation * Energy * Smart city services * Education * Social services, unemployment and homelessness * Healthcare * Ethical issues, fairness and accountability * Trustability and interpretability * Topics aligned with the UN development goals: www.un.org/sustainabledevelopment/sustainable-development-goals/
The major selection criteria will be the novelty of the application and its social impact.
We are also interested in applications that have built a successful business model and are able to sustain themselves economically. Most Social Good applications have been carried out by non-profit and charity organisations, conveying the idea that Social Good is a luxury that only societies with a surplus can afford. We would like to hear from successful projects, which may not be strictly “non-profit” but have Social Good as their main focus.
There will be an award for the best paper.
Paper submission: Authors should submit a PDF version in Springer LNCS style using the workshop EasyChair site:https://easychair.org/my/conference?conf=sogood2020. The maximum length of papers is 16 pages, consistent with the ECML PKDD conference submissions.
Submitting a paper to the workshop means that if the paper is accepted, at least one author will attend the workshop and present the paper. Papers not presented at the workshop will not be included in the proceedings.
In light of COVID-19, we will follow ECML PKDD’s policy for attendance and presentation (face-to-face, virtual or hybrid). ECML PKDD is considering contingency plans and will announce its final decision before the early registration deadline (second half of July).
Paper publication: The proceedings of the workshop will be published either by Springer as a Lecture Notes volume or by CEUR in their workshop proceedings series (ceur-ws.org/). Selected workshop papers will be invited for extension and submission to a special journal issue.
Workshop format: * Full-day workshop * 1-2 keynote talks, speakers to be announced * Oral presentation of accepted papers * Panel discussion with the audience
Important Dates: * Workshop paper submission deadline: June 11, 2020 * Workshop paper acceptance notification: July 2, 2020 * Workshop paper camera-ready deadline: July 16, 2020 * Workshop: September 14 or 18, 2020 (TBC)
Program Committee members (more to be added): * Carlos Ferreira, ISEP, Portugal * Marta Arias, UPC BarcelonaTech, Spain * Albert Bifet, Telecom ParisTech, France * José del Campo-Ávila, University of Malaga, Spain * Hau Chan, University of Nebraska-Lincoln * Itziar de Lecuona, University of Barcelona, Spain * Yann-Ael Le Borgne, University Libre Bruxelles * José del Campo, University of Málaga, Spain * Jeremiah Deng, University of Otago, New Zealand * Cèsar Ferri, Technical University of Valencia, Spain * Geoffrey Holmes, University of Waikato, New Zealand * Konstantin Kutzkov, Amalfi Analytics, Spain * Josep-Lluís Larriba-Pey, UPC BarcelonaTech, Spain * Rafael Morales-Bueno, University of Málaga, Spain * Nuno Moniz, INESC TEC, Porto, Portugal * Ana Nogueira, INESC TEC, Porto, Portugal * Alexandra Olteanu, Microsoft Research, USA * Panagiotis Papapetrou, Stockholm University, Sweden * Maria Pedroto, INESC TEC, Porto, Portugal * Sonia Teixeira, INESC TEC, Porto, Portugal * Emma Tonkin, University of Bristol, UK * Alicia Troncoso, University Pablo de Olavide, Spain * Evgueni Smirnov, University of Maastricht, The Netherlands * Kristina Yordanova, University of Rostock, Germany * Martí Zamora, UPC BarcelonaTech, Spain
Organizers: * Ricard Gavaldà (UPC BarcelonaTech, Spain),gavalda@cs.upc.edu <mailto:gavalda@cs.upc.edu> * Irena Koprinska (University of Sydney, Australia),irena.koprinska@sydney.edu.au <mailto:irena.koprinska@sydney.edu.au> * João Gama (University of Porto, Portugal),jgama@fep.up.pt <mailto:jgama@fep.up.pt> * Rita Ribeiro (University of Porto, Portugal),rpribeiro@fc.up.pt <mailto:rpribeiro@fc.up.pt>
Carlos Ferreira
ISEP | Instituto Superior de Engenharia do Porto Rua Dr. António Bernardino de Almeida, 431 4249-015 Porto – PORTUGAL tel. +351 228 340 500 | fax +351 228 321 159 mail@isep.ipp.pt | www.isep.ipp.pt

Caros APPIAnos,
Está a decorrer uma consulta pública sobre um “White Paper on Artificial Intelligence – a European Approach” aberta a todos os agentes relacionados com IA. Deixo aqui o link caso pretendam contribuir com sugestões e divulgar por outros potenciais interessados.
ec.europa.eu/info/law/better-regulation/have-your-say/initiatives/12270-White-Paper-on-Artificial-Intelligence-a-European-Approach/public-consultation
Alípio Jorge

Workshop on BIG DATA & DEEP LEARNING in HIGH PERFORMANCE COMPUTING (BDL2020) (sbac2020.dcc.fc.up.pt/bdl2020/)
in conjunction with the IEEE 32nd International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD 2020) (sbac2020.dcc.fc.up.pt/)
September 9, 2020, Porto, Portugal
—————————————————————————- ** NEW ** BDL2020 will be held online (synchronous and/or asynchronous) —————————————————————————-
We are monitoring the Coronavirus disease (COVID-19) outbreak and following the recommendations/guidelines from the World Health Organization (WHO) and the European Centre for Disease Prevention and Control (ECDC).
The safety of all conference participants is our main priority. In this perspective, regardless of the outbreak outcomes in September, we will make BDL2020 an online (synchronous and/or asynchronous) event and we will maintain the regular publication activities, i.e., accepted papers will be eligible for publication at the IEEE Xplore.
The Workshop fee is now 200 euros.
———————————— WORKSHOP ON BIG DATA & DEEP LEARNING IN HIGH PERFORMANCE COMPUTING ————————————
The number of very large data repositories (big data) is increasing in a rapid pace. Analysis of such repositories using the “traditional” sequential implementations of ML and emerging techniques, like deep learning, that model high-level abstractions in data by using multiple processing layers, requires expensive computational resources and long running times. Parallel or distributed computing are possible approaches that can make analysis of very large repositories and exploration of high-level representations feasible. Taking advantage of a parallel or a distributed execution of a ML/statistical system may: i) increase its speed; ii) learn hidden representations; iii) search a larger space and reach a better solution or; iv) increase the range of applications where it can be used (because it can process more data, for example). Parallel and distributed computing is therefore of high importance to extract knowledge from massive amounts of data and learn hidden representations.
The workshop will be concerned with the exchange of experience among academics, researchers and the industry whose work in big data and deep learning require high performance computing to achieve goals. Participants will present recently developed algorithms/systems, on going work and applications taking advantage of such parallel or distributed environments.
———————————— LIST OF TOPICS ————————————
All novel data-intensive computing techniques, data storage and integration schemes, and algorithms for cutting-edge high performance computing architectures which targets Big Data and Deep Learning are of interest to the workshop. Examples of topics include but not limited to: – parallel algorithms for data-intensive applications; – scalable data and text mining and information retrieval; – using Hadoop, MapReduce, Spark, Storm, Streaming to analyze Big Data; – energy-efficient data-intensive computing; – deep-learning with massive-scale datasets; – querying and visualization of large network datasets; – processing large-scale datasets on clusters of multicore and manycore processors, and accelerators; – heterogeneous computing for Big Data architectures; – Big Data in the Cloud; – processing and analyzing high-resolution images using high-performance computing; – using hybrid infrastructures for Big Data analysis. – New algorithms for parallel/distributed execution of ML systems; – applications of big data and deep learning to real-life problems.
———————————— KEY DATES ————————————
Deadline for paper submission: May 25, 2020
Author notification: July 1, 2020
Camera-ready version of papers: July 25, 2020
———————————— SUBMISSION ————————————
We invite authors to submit original work to BDL. All papers will be peer reviewed and accepted papers will be published in IEEE Xplore.
Submissions must be in English, limited to 8 pages in the IEEE conference format (see www.ieee.org/conferences/publishing/templates.html)
All submissions should be made electronically through the EasyChair system: easychair.org/conferences/?conf=bdl2020
———————————— REGISTRATION ————————————
A full registration to the workshop and presentation are needed in order to have your paper included in the workshop proceedings.
The Workshop fee is 200 euros.
Registration system available in sbac2020.dcc.fc.up.pt/bdl2020/registration.html
———————————— VENUE ————————————
Department of Computer Science, Faculty of Sciences, University of Porto
Rua do Campo Alegre 1021/1055 4169-007 Porto, Portugal
The city of Porto is famous for its Port wine and beautiful scenery, architecture and cultural events.
Portugal has again been awarded the best European Tourist Destination by the World Travel Awards, the Oscars equivalent in the field of tourism.
———————————— ORGANIZATION ————————————
Carlos Ferreira (LIAAD – INESC TEC LA and Polytechnic Institute of Porto) João Gama (LIAAD – INESC TEC LA and University of Porto) Albert Bifet (Telecom ParisTech) Miguel Areias (CRACS – INESC TEC LA and University of Porto) Rui Camacho (LIAAD -INESC TEC LA and University of Porto)

Carlos Ferreira
ISEP | Instituto Superior de Engenharia do Porto Rua Dr. António Bernardino de Almeida, 431 4249-015 Porto – PORTUGAL tel. +351 228 340 500 | fax +351 228 321 159 mail@isep.ipp.pt | www.isep.ipp.pt