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IFIP WG 7.3 PERFORMANCE 2023: Call for Papers and Workshops
May 16th, 2023 
Daniela Lopez de Luise Summer School Course on Collective Decision Making course in Jyvaskyla, Finland, in August 2023 – Registration closes on May 19, 2023
May 16th, 2023 Daniela Lopez de Luise
The International 32nd Jyvaskyla Summer School will be organized in August 2023 at the University of Jyväskylä, Finland (https://jyu.fi/jss).
You are warmly invited to register for the course “Collective Decision Making”.
Course: Collective Decision Making (2 ects)
Lecturer: Prof. Dr. Rudolf Vetschera (University of Vienna, Austria)
Time: August 14-18, 2023
Contents: This course covers a wide range of approaches to decision making by multiple persons, whose interests might or might not be aligned with each other. Specifically, methods and models of social choice theory, group decision making and negotiations will be covered.
Learning outcomes: Students should obtain a deeper understanding of fundamental problems in decision situations that involve multiple stakeholders and the analytical tools to analyze such situations and provide possible recommendations to the involved parties.
Prerequisites: Basic knowledge of concepts of decision analysis and operations research.
Targeted at: advanced MSc students, doctoral students and also post-doctoral researchers who are interested in getting a compact but comprehensive knowledge of different aspects of group decision-making.
Although the official application period has ended. applicants are still accepted until May 19th
Participation in all Summer School courses is free of charge. Participants are responsible for covering their own meals, accommodation and all costs related to travel as well as possible visa costs.
Application: Send your CV and a very brief motivation to babooshka.b.shavazipour@jyu.fi.
Final (exceptional) deadline for applications (for this course) is 19th of May 2023!
Call For Papers – 4 th International Conference… was uploaded by International Journal of Chaos, Control, Modelling and Simulation (IJCCMS)
May 16th, 2023 Daniela Lopez de Luise
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International Journal of Chaos, Control,…ACM MM 2023 – ACM Multimedia Conference call for Brave New Ideas (BNI)
May 16th, 2023 Daniela Lopez de Luise
ACM Multimedia invites researchers and practitioners from all over the world to submit their innovative papers to the Brave New Ideas (BNI) Track of ACM Multimedia 2023. The BNI track aims to promote new and visionary ideas that can lead the multimedia research community towards new directions and challenges. We are looking for papers that challenge the status quo and present new and creative perspectives on multimedia research.
The BNI track seeks visionary ideas that have the potential for high impact, while still being high risk. Papers may introduce new research areas or approaches, propose new applications, paradigms, and perspectives, and stimulate discussions in the research community.
TOPICS:
Papers submitted to the BNI track can take one of three approaches:
- an extensive meta-review of existing work that supports the feasibility of the idea;
- an extensive review of existing work that highlights shortcomings in current research approaches;
- (light) experimental or theoretical validation of the paper’s BNI thesis.
We encourage submissions that propose new ideas, even if they do not have large-scale experimental results or comparisons to the state-of-the-art.
SUBMISSIONS:
Submissions should not exceed six pages (excluding references and supplementary material) and should be submitted to the “Brave New Ideas” Track for consideration. For more information on submission guidelines and format, please refer to the main conference call for papers (https://www.acmmm2023.org/cfp/). Submissions are double-blind and will be reviewed by a set of independent reviewers, and the decisions will be made on the basis of their feedback. Review criteria are scientific impact, intellectual rigor, and a compelling case for the paper to be innovative in the sense described above.
SUBMISSION SITE:
https://openreview.net/group?id=acmmm.org/ACMMM/2023/Track/Brave_New_Ideas
IMPORTANT DATES:
Submission deadline: 7th June 2023 11:59 p.m GMT
Submission site opens: 20th May 2023 11:59 p.m. GMT
Notification of Acceptance: 15th July, 2023
Camera Ready deadline: 31st July, 2023
BRAVE NEW IDEAS CHAIRS
Simone Calderara, University of Modena and Reggio Emilia
Liquiang Nie Harbin Institute of Technology (Shenzhen).
Pedestrian Attribute Recognition (PAR) Contest 2023 – CAIP 2023
May 16th, 2023 Daniela Lopez de Luise Pedestrian Attribute Recognition (PAR) Contest 2023 - CAIP 2023 === Call for submissions === Pedestrian Attribute Recognition (PAR) Contest 2023 International Conference on Computer Analysis of Images and Patterns CAIP 2023 Website: https://mivia.unisa.it/par2023/ or https://par2023.unisa.it ======================== === Important dates === Submission Deadline: June 30th, 2023 ======================== === Contest === We are pleased to announce that Pedestrian Attribute Recognition (PAR) Contest 2023 will be held by the 20th International Conference on Computer Analysis of Images and Patterns CAIP 2023. The Pedestrian Attribute Recognition (PAR) Contest is a competition among methods for pedestrian attributes recognition from images. For the contest, we propose the use of a novel training set, the MIVIA PAR Dataset, partially annotated with five pedestrian attributes, namely color of the clothes (top and bottom), gender (female, male), bag (y/n), hat (y/n), and we restrict the competition to methods based on multi-task learning. The participants are encouraged to use additional samples or to produce themselves the missing annotations; this possibility is allowed in the competition only under the constraint that the additional samples and annotations are made publicly available, to give a relevant contribution to the diffusion of public datasets for pedestrian attributes recognition. After the contest, the dataset, also augmented with additional samples and annotations produced by the participants, will be made publicly available for the scientific community and will hopefully become among the biggest dataset of pedestrian attributes with this set of annotations. The performance of the competing methods will be evaluated in terms of accuracy on a private test set composed by images that are different from the ones available in the training set. ======================== === Rules === The deadline for the submission of the methods is 30th June, 2023. The submission must be done with an email in which the participants share (directly or with external links) the trained model, the code and the report. The participants can receive the training set, the validation set and their annotations by sending an email to par2023@unisa.it, in which they also communicate the name of the team. The participants can use these training and validation samples and annotations, but they can also use additional samples and/or add the missing labels, under the constraint that they make the additional samples and annotations publicly available. The participants must provide, for each sample, the prediction for all the considered pedestrian attributes, by training their multi-task neural network. For this reason, the validation set contains only fully annotated pedestrian samples. The teams are free to design novel neural network architectures or to define novel training procedures and loss functions for multi-task learning. Particularly welcome are the methods dealing with the missing labels. The participants must submit their trained model and their code by carefully following the detailed instructions reported in the website. The participants are strongly encouraged to submit a contest paper to CAIP 2023, whose deadline is 10th July, 2023. The contest paper must be also sent by email to the organizers. Otherwise, the participants must produce a brief PDF report of the proposed method. The detailed instructions of the proposed method can be downloaded here: https://mivia.unisa.it/par2023/ (or https://par2023.unisa.it). ======================== The organizers, Antonio Greco Bruno Vento