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Association for the Advancement of Artificial Intelligence • 1101 Pennsylvania Ave, NW, Suite 340, Washington, District of Columbia 20004, United States
January 5th, 2023
Daniela Lopez de Luise
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Association for the Advancement of Artificial Intelligence • 1101 Pennsylvania Ave, NW, Suite 340, Washington, District of Columbia 20004, United States
January 5th, 2023
Daniela Lopez de Luise DeepLearn 2023 Summer
Las Palmas de Gran Canaria, Spain
July 17-21, 2023
https://irdta.eu/deeplearn/2023su/
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Co-organized by:
University of Las Palmas de Gran Canaria
Institute for Research Development, Training and Advice – IRDTA
Brussels/London
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Early registration: January 21, 2023
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FRAMEWORK:
DeepLearn 2023 Summer is part of a multi-event called Deep&Big 2023 consisting also of BigDat 2023 Summer. DeepLearn 2023 Summer participants will have the opportunity to attend lectures in the program of BigDat 2023 Summer as well if they are interested.
SCOPE:
DeepLearn 2023 Summer will be a research training event with a global scope aiming at updating participants on the most recent advances in the critical and fast developing area of deep learning. Previous events were held in Bilbao, Genova, Warsaw, Las Palmas de Gran Canaria, Guimarães, Las Palmas de Gran Canaria, Luleå, Bournemouth and Bari.
Deep learning is a branch of artificial intelligence covering a spectrum of current frontier research and industrial innovation that provides more efficient algorithms to deal with large-scale data in a huge variety of environments: computer vision, neurosciences, speech recognition, language processing, human-computer interaction, drug discovery, health informatics, medical image analysis, recommender systems, advertising, fraud detection, robotics, games, finance, biotechnology, physics experiments, biometrics, communications, climate sciences, geographic information systems, signal processing, genomics, etc. etc. Renowned academics and industry pioneers will lecture and share their views with the audience.
Most deep learning subareas will be displayed, and main challenges identified through 16 four-hour and a half courses and 2 keynote lectures, which will tackle the most active and promising topics. The organizers are convinced that outstanding speakers will attract the brightest and most motivated students. Face to face interaction and networking will be main ingredients of the event. It will be also possible to fully participate in vivo remotely.
An open session will give participants the opportunity to present their own work in progress in 5 minutes. Moreover, there will be two special sessions with industrial and employment profiles.
ADDRESSED TO:
Graduate students, postgraduate students and industry practitioners will be typical profiles of participants. However, there are no formal pre-requisites for attendance in terms of academic degrees, so people less or more advanced in their career will be welcome as well. Since there will be a variety of levels, specific knowledge background may be assumed for some of the courses. Overall, DeepLearn 2023 Summer is addressed to students, researchers and practitioners who want to keep themselves updated about recent developments and future trends. All will surely find it fruitful to listen to and discuss with major researchers, industry leaders and innovators.
VENUE:
DeepLearn 2023 Summer will take place in Las Palmas de Gran Canaria, on the Atlantic Ocean, with a mild climate throughout the year, sandy beaches and a renowned carnival. The venue will be:
Institución Ferial de Canarias
Avenida de la Feria, 1
35012 Las Palmas de Gran Canaria
STRUCTURE:
2 courses will run in parallel during the whole event. Participants will be able to freely choose the courses they wish to attend as well as to move from one to another.
Also, if interested, participants will be able to attend courses developed in BigDat 2023 Summer, which will be held in parallel and at the same venue.
Full live online participation will be possible. The organizers highlight, however, the importance of face to face interaction and networking in this kind of research training event.
KEYNOTE SPEAKERS: (to be completed)
Aidong Zhang (University of Virginia), Concept-Based Models for Robust and Interpretable Deep Learning
PROFESSORS AND COURSES: (to be completed)
Eneko Agirre (University of the Basque Country), [introductory/intermediate] Natural Language Processing in the Large Language Model Era
Tae-Kyun Kim (Korea Advanced Institute of Science and Technology), [intermediate/advanced] Deep 3D Pose Estimation
Marcus Liwicki (Luleå University of Technology), [intermediate/advanced] Methods for Learning with Few Data
Ivan Oseledets (Skolkovo Institute of Science and Technology), [tba] Tensor Methods for Approximation of High-Dimensional Arrays and Their Applications in Machine Learning
Carlo Sansone (University of Naples Federico II), tba
Ponnuthurai N. Suganthan (Nanyang Technological University), [introductory/intermediate] Randomization-Based Deep and Shallow Learning Algorithms and Architectures
Savannah Thais (Columbia University), [intermediate] Applications of Graph Neural Networks: Physical and Societal Systems
Z. Jane Wang (University of British Columbia), [introductory/intermediate] Adversarial Deep Learning in Digital Image Security & Forensics
Li Xiong (Emory University), [introductory] Deep Learning and Privacy Enhancing Technology
Lihi Zelnik-Manor (Technion – Israel Institute of Technology), [introductory] Introduction to Computer Vision and the Ethical Questions It Raises
OPEN SESSION:
An open session will collect 5-minute voluntary presentations of work in progress by participants. They should submit a half-page abstract containing the title, authors, and summary of the research to david@irdta.eu by July 9, 2023.
INDUSTRIAL SESSION:
A session will be devoted to 10-minute demonstrations of practical applications of deep learning in industry. Companies interested in contributing are welcome to submit a 1-page abstract containing the program of the demonstration and the logistics needed. People in charge of the demonstration must register for the event. Expressions of interest have to be submitted to david@irdta.eu by July 9, 2023.
EMPLOYER SESSION:
Organizations searching for personnel well skilled in deep learning will have a space reserved for one-to-one contacts. It is recommended to produce a 1-page .pdf leaflet with a brief description of the organization and the profiles looked for to be circulated among the participants prior to the event. People in charge of the search must register for the event. Expressions of interest have to be submitted to david@irdta.eu by July 9, 2023.
ORGANIZING COMMITTEE:
Carlos Martín-Vide (Tarragona, program chair)
Sara Morales (Brussels)
David Silva (London, organization chair)
REGISTRATION:
It has to be done at
https://irdta.eu/deeplearn/2023su/registration/
The selection of 8 courses requested in the registration template is only tentative and non-binding. For logistical reasons, it will be helpful to have an estimation of the respective demand for each course. During the event, participants will be free to attend the courses they wish as well as eventually courses in BigDat 2023 Summer.
Since the capacity of the venue is limited, registration requests will be processed on a first come first served basis. The registration period will be closed and the on-line registration tool disabled when the capacity of the venue will have got exhausted. It is highly recommended to register prior to the event.
FEES:
Fees comprise access to all courses and lunches. There are several early registration deadlines. Fees depend on the registration deadline.
The fees for on site and for online participation are the same.
ACCOMMODATION:
Accommodation suggestions will be available in due time at
https://irdta.eu/deeplearn/2023su/accommodation/
CERTIFICATE:
A certificate of successful participation in the event will be delivered indicating the number of hours of lectures.
Participants will be recognized 2 ECTS credits by University of Las Palmas de Gran Canaria.
QUESTIONS AND FURTHER INFORMATION:
ACKNOWLEDGMENTS:
Cabildo de Gran Canaria
Universidad de Las Palmas de Gran Canaria – Fundación Parque Científico Tecnológico
Universitat Rovira i Virgili
Institute for Research Development, Training and Advice – IRDTA, Brussels/London
Computer Vision and Machine Learning (CVML) email list www page: https://lists.auth.gr/sympa/info/cvml
January 5th, 2023
Daniela Lopez de Luise We are organizing the next iteration of the Adaptive and Learning Agents (ALA) workshop at the International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2023) in London, United Kingdom. Please find the Call for Papers below.
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Adaptive and Learning Agents Workshop at AAMAS (London, United Kingdom)
https://alaworkshop2023.github.io/
Submission deadline: January 30, 2023
Extended versions of all original contributions at ALA 2023 will be eligible for inclusion in a special issue of the Springer journal Neural Computing and Applications (Impact Factor 5.606).
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TL;DR:
* Workshop with a long and successful history, now in its thirteenth edition.
* Covering all aspects of adaptive and learning agents and multi-agent systems research.
* Open to original research papers, work-in-progress, and visionary outlook papers, as well as presentations on recently published journal papers.
* ACM proceedings (AAMAS) format up to 8 pages (excluding references) for original research, up to 6 pages for work-in-progress and outlook papers (shorter papers are also welcome and will not be judged differently) and 2 pages for recently published journal papers.
* Accepted papers are eligible for inclusion in a post-proceedings journal special issue.
* Submissions through EasyChair: https://easychair.org/my/conference?conf=ala2023
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IMPORTANT DATES:
* Submission Deadline: January 30, 2023
* Notification of acceptance: February 27, 2023
* Camera-ready copies: March 5, 2023
* Workshop: May 29 & 30, 2023
* Journal submission deadline: September 15, 2023
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OVERVIEW
Adaptive and learning agents, particularly those interacting with each other in a multi-agent setting, are becoming increasingly prominent as the size and complexity of real-world systems grows. How to adaptively control, coordinate and optimize such systems is an emerging multi-disciplinary research area at the intersection of Computer Science, Control Theory, Economics, and Biology. The ALA workshop will focus on agents and multi-agent systems which employ learning or adaptation.
The goal of this workshop is to increase awareness of and interest in adaptive agent research, encourage collaboration and give a representative overview of current research in the area of adaptive and learning agents and multi-agent systems. It aims at bringing together not only scientists from different areas of computer science but also from different fields studying similar concepts (e.g., game theory, bio-inspired control, mechanism design).
All aspects of adaptive and learning agents and multi-agent systems are on topic for this workshop, but we will particularly encourage work that modifies established learning techniques and/or creates new learning paradigms to address the many challenges presented by complex real-world problems. The topics of interest include (but are not limited to):
* Novel combinations of reinforcement and supervised learning approaches
* Integrated learning approaches using reasoning modules like negotiation, trust, coordination, etc.
* Supervised and semi-supervised multi-agent learning
* Reinforcement learning in multi-agent systems
* Novel deep learning approaches for adaptive single and multi-agents systems
* Human-in-the-loop learning systems
* Planning and Reasoning (single and multi-agent)
* Distributed learning
* Adaptation and learning in dynamic environments
* Evolution and Co-evolution of agents in complex multi-agent environments
* Cooperative exploration
* Learning to cooperate and collaborate
* Learning trust and reputation
* Communication restrictions and their impact on multi-agent coordination
* Design of reward structure and fitness measures for coordination
* Scaling learning techniques to large systems of agents
* Emergent behavior in adaptive multi-agent systems
* Game theoretical analysis of adaptive multi-agent systems
* Neuro-control for adaptation in multi-agent systems
* Bio-inspired multi-agent systems
* Adaptive and learning agents for multi-objective decision making
* Multiple objectives in (multi-)agent systems
* Applications of adaptive and learning (multi-agent) systems to model real world complex systems
In addition to these topics, this year we are interested in exploring negative results that can serve as guidelines for early-stage researchers in the field of adaptive and learning single/multi-agent systems.
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SUBMISSION DETAILS
Papers can be submitted through EasyChair: https://easychair.org/my/conference?conf=ala2023
We invite submission of original work, up to 8 pages in length (excluding references) in the ACM proceedings format (i.e. following the AAMAS formatting instructions). This includes work that has been accepted as a poster/extended abstract at the AAMAS 2023 conference. Additionally, we welcome submission of preliminary results, i.e. work-in-progress, as well as visionary outlook papers that lay out directions for future research in a specific area, both up to 6 pages in length, although shorter papers are very much welcome, and will not be judged differently. Finally, we also accept recently published journal papers in the form of a 2 page abstract.
All submissions will be peer-reviewed (single-blind). Accepted work will be allocated time for poster and possibly oral presentation during the workshop. Extended versions of all original contributions at ALA 2023 will be eligible for inclusion in a special issue of the Springer journal Neural Computing and Applications (Impact Factor 5.606). Deadline for submitting extended papers: September 15, 2023.
We look forward to receiving your submissions,
– The Organizers
Conor F. Hayes (University of Galway, IE)
Caroline Wang (The University of Texas at Austin, USA)
Connor Yates (Oregon State University, USA)
Francisco Cruz (UNSW Sydney, AUS)
January 5th, 2023
Daniela Lopez de Luise
UAI 2023 – Call for Papers
The Conference on Uncertainty in Artificial Intelligence (UAI) is one of the premier international conferences on research related to learning and reasoning in the presence of uncertainty. The conference has been held every year since 1985. The upcoming 39th edition (UAI 2023) will be an in-person conference with virtual elements taking place in Pittsburgh, Pennsylvania, USA from 31 July to 4 August 2023.
We invite papers that describe novel theory, methodology and applications related to artificial intelligence, machine learning and statistics. Papers will be assessed in a rigorous double-blind peer-review process, based on the criteria of technical correctness, novelty, clarity of writing, and potential impact. Authors are strongly encouraged to make code and data available.
All accepted papers will be presented in poster sessions and spotlight presentations (physically or remotely). Selected papers will have longer presentations and an assigned discussant to foster debate. All accepted papers will be published in a volume of Proceedings of Machine Learning Research (PMLR).
Deadlines and other relevant dates can be found under important dates.
Important dates for authors:
Papers should be submitted on OpenReview at https://openreview.net/group?id=auai.org/UAI/2023/Conference.
We are looking forward to building an exciting program and we aim to make the most of the advantages that a hybrid conference can create. If you have any particular positive or negative experiences that you would like to share with us, please do not hesitate to email us.
If you are interested in giving a tutorial or organising a workshop at UAI 2023, please contact the tutorial chairs (uai2023chairs+tutorials@gmail.com) or workshop chairs (uai2023chairs+workshop@gmail.com) by 10 March 2023.
Relevant dates:
Robin Evans and Ilya Shpitser
UAI 2023 Program Chairs
uai2023programchairs@gmail.com
January 5th, 2023
Daniela Lopez de Luise We cordially invite You to
International Symposium on Fuzzy Sets (isfspolfuzz.ur.edu.pl)
which will be organized by
Polish Society for Fuzzy Sets (POLFUZZ)
&
University of Rzeszów
in cooperation with the Slovak University of Technology (STU) in Bratislava.
The ISFS'2023 will be May 19 – 21, 2023
at University of Rzeszów, Pigonia 1 in Rzeszów (Poland).
ISFS'2023 is the first conference organized by the Polish Society for Fuzzy Sets, which was established in 2022 to associate the Polish community dealing with the theory and application of fuzzy set theory (POLFUZZ, https://polfuzz.org).
Aims and Scope of the ISFS'2023:
The conference will provide an excellent international forum for sharing knowledge and results in theory, methodology, and applications of Fuzzy Sets and Systems.
Formation of a platform for discussion of critical research environments and disciplines. Indication of the need for changes in the cooperation of the scientific community and with business partners.
Research presentations are of interest in the following topics:
• Theoretical foundations of fuzzy logic and fuzzy set theory;
• Imprecise information modeling with fuzzy, rough, and other methods;
• Federated learning;
• Image processing and computer vision;
• Information retrieval;
• Knowledge representation and engineering;
• Decision-making models;
• Expert systems;
• Intelligent data analysis and data mining;
• Approximate reasoning.
Potential areas of application, among others, include:
• Medical and Healthcare systems;
• Business Process Modeling;
• Social and economic models.
Submission guidelines:
All submitted papers will be peer-reviewed.
Papers can be submitted in either 1-2 page(s) abstract.
Papers must show the scientific results, be original, and may not be published elsewhere.
After the Conference, accepted papers/abstracts will be published in the post-conference edition by the University of Rzeszów Publisher with ISBN.
The best papers and abstracts will be invited and recommended to extend their contributions to internationally recognized journals.
It will be a pleasure to host you in Rzeszów, I encourage you to visit the conference website: isfspolfuzz.ur.edu.pl
Best regards,
Barbara Pekala
on behalf of the POLFUZZ & the ISFS Organizing Committee