Machine-learning-nederland May 2024

machine-learning-nederland@list.uva.nl

5 participants
5 discussions

[2nd CfP] Multi-Objective Decision Making Workshop (MODeM 2024) at ECAI 2024
by Radulescu, R.T. (Roxana) 27 May '24

27 May '24

2nd CfP: Multi-Objective Decision Making Workshop (MODeM 2024) at ECAI 2024 ------------------------------------------------------------------------------------------------------------- TLDR * Following on from successful previous editions that were held virtually in 2021<https://modem2021.cs.universityofgalway.ie/> and in person at ECAI in 2023<https://modem2023.vub.ac.be/>, the Multi-Objective Decision Making 2024 (MODeM 2024) workshop will be held in person again this year at ECAI 2024, on 19/20 October in Santiago de Compostela, Spain. * MODeM 2024 covers all aspects of multi-objective/multi-criteria/multi-attribute decision making in relation to intelligent systems and autonomous agents * After the workshop, there will be a topical collection on Multi-Objective Decision Making 2024 in the journal Neural Computing & Applications<https://link.springer.com/journal/521> (NC&A, impact factor 6.0, one of the top 10 journals in AI on Google Scholar Metrics): https://link.springer.com/journal/521/updates/26958874 * Further details are available on the workshop website: https://modem2024.vub.ac.be/ * MODeM 2024 Workshop paper deadline: 15 June 2024 (23:59 AoE) ------------------------------------------------------------------------------------------------------------- Explicitly modelling multiple objectives can be essential for decision support, explainability, and human-AI alignment. As such, there has been a growing awareness of the need for automated and assistive decision making systems to move beyond single-objective formulations when dealing with complex real-world issues, which invariably involve multiple competing objectives. In this workshop, we aim to provide a platform for original research in multi-objective decision making using AI. The workshop targets high-quality original papers covering all aspects of multi-objective decision making, including, but not limited to, the list of topics below. Topics The following is a non-exhaustive list of topics that we would like to cover in the workshop: * Multi-objective/multi-criteria/multi-attribute decision making * Multi-objective reinforcement learning * Multi-objective planning and scheduling * Multi-objective multi-agent decision making * Multi-objective game theory * Multi-objective/multi-criteria/multi-attribute utility theory * Preference elicitation for MODeM * Social choice and MODeM * Multi-objective decision support systems * Multi-objective metaheuristic optimisation (e.g. evolutionary algorithms) for autonomous agents and multi-agent systems * Multi-objectivisation * Human-AI alignment through multi-objective modelling * Ethical AI through multi-objective modelling * Explainable AI through multi-objective modelling * Interactive systems for MODeM * Applications of MODeM * Interdisciplinary work (MODeM research that relates to other fields) * New benchmark problems for MODeM Important Dates Submissions deadline: 15 June 2024 (23:59 AoE) Notification of acceptance: 06 August 2024 Camera-ready copies: 13 August 2024 Workshop: 19 or 20 October 2024 (TBA) Submission details Papers should be formatted according to the ECAI 2024 guidelines<https://www.ecai2024.eu/calls/main-track>, and should be a maximum of 7 pages in length (with additional pages containing references only). Shorter papers (up to 5 pages) reporting preliminary results and work-in-progress are also welcome. Submissions should report original work that has not previously been published elsewhere. Finally, we also welcome summaries of recently published journal papers in the form of a 2-page abstract. All submissions will be peer-reviewed (double-blind). Accepted work will be allocated time for oral and/or poster presentation during the workshop. Papers can be submitted through Microsoft CMT: https://cmt3.research.microsoft.com/MODeM2024 Topical Collection on Multi-Objective Decision Making 2024 After the workshop, all original contributions presented at MODeM 2024 will be invited to submit substantially improved and extended versions of their work, for consideration to be published in a post-proceedings topical collection (TC) of the Springer journal Neural Computing & Applications<https://www.springer.com/journal/521> (NC&A, impact factor 6.0, one of the top 10 journals in AI on Google Scholar Metrics): https://link.springer.com/journal/521/updates/26958874 Organising Committee Patrick Mannion (University of Galway, IE) Roxana Rădulescu (Utrecht University, NL; Vrije Universiteit Brussel, BE) Willem Röpke (Vrije Universiteit Brussel, BE) Pieter Libin (Vrije Universiteit Brussel, BE) Senior Advisory Committee Ali E. Abbas (University of Southern California, USA) Carlos A. Coello Coello (CINVESTAV-IPN, MX) Richard Dazeley (Deakin University, AU) Enda Howley (University of Galway, IE) Ann Nowé (Vrije Universiteit Brussel, BE) Patrice Perny (UPMC, FR) Marcello Restelli (Politecnico di Milano, IT) Diederik M. Roijers (Vrije Universiteit Brussel, BE; City of Amsterdam, NL) Peter Vamplew (Federation University Australia, AU) Nic Wilson (University College Cork, IE) Program Committee If you are interested in serving on the programme committee please get in touch with the organisers at: modem.organisers AT gmail.com

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Call for Participation in Learning Theory Mentorship Workshop
by Tim van Erven 21 May '24

21 May '24

Dear all, I am forwarding the announcement below on behalf of Ciara Pike-Burne. NB This is an excellent opportunity to get advice from internationally top researchers in learning theory. Best, Tim ——————————————————————————— Hi all, We are pleased to invite you to the 6th Learning Theory Alliance Mentorship workshop <https://let-all.com/spring24.html>, to be held on *June 4-5, 2024*. The workshop is *free and fully virtual*. The workshop is intended for upper-level undergraduate and all-level graduate students as well as postdoctoral researchers who are interested in theoretical computer science and machine learning. No prior research experience in the field is expected, and some sessions may be of interest to researchers in adjacent fields. We have several planned events including: * A “how-to” talk on how to be a good collaborator (discussing what healthy collaborations do and don’t look like, setting expectations, transitioning from junior to senior collaborator roles). * A “how-to” talk on how to do theory research (covering topics such as formulating research questions and theory problems, breaking a larger problem into smaller toy problems, and day-to-day best practices). * A panel discussion on time management (for example, maintaining a balance between learning and solving, work-life balance, deciding how many projects to work on). * A social hour with mentoring tables. Our lineup includes Shuchi Chawla (UT), Adam Groce (Reed College), Zhiyi Huang (University of Hong Kong), Varun Kanade (Oxford), Po-Ling Loh (University of Cambridge), Audra McMillan (Apple), Ankur Moitra (MIT), Devi Parikh (Georgia Tech), Aaditya Ramdas (CMU), and Steven Wu (CMU). A short application form <https://forms.gle/ACZBLto6MweLd9dc6> is required to participate with an application deadline of *Tuesday, May 28, 2024*. Students with backgrounds that are underrepresented or underserved in related fields are especially encouraged to apply. We are trying our best to accommodate all time zones. More information (including the schedule) can be found on the event’s website: https://let-all.com/spring24.html. This workshop is part of our broader community-building initiative called the Learning Theory Alliance. Check out http://let-all.com/ for more details. To connect with fellow participants and stay in touch for more announcements, we encourage everyone to join <https://join.slack.com/t/learningtheor-cui5258/shared_invite/zt-2421d3wfl-o…> the LeT-All slack. Best, Ciara Pike-Burke, Vatsal Sharan, Ellen Vitercik, and Lydia Zakynthinou LeT-All’s Mentoring Workshop Committee

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[IECMA 2024] Join us today by registering to The 2nd International Electronic Conference on Machines and Applications (IECMA 2024)!
by Charlene Dong 21 May '24

21 May '24

Dear Colleagues, It is our pleasure to invite you to join the 2nd International Electronic Conference on Machines and Applications (IECMA 2024) after the strong success of the previous annual online conference. IECMA 2024 will be held online from 18 to 20 June 2024. https://sciforum.net/event/IECMA2024?utm_source=google&utm_medium=email+&ut… The scope of this online conference is to bring together well-known worldwide experts who are currently working on machinery and engineering and to provide an online forum for presenting and discussing new results. We would like to invite you to join us today by registering to IECMA 2024 FREE, where you can engage in cutting-edge discussions and networking opportunities. Please visit the following link to complete your registration: https://sciforum.net/event/IECMA2024?section=#registration. If you encounter any difficulties during the registration process, please do not hesitate to contact us. If you have already registered, kindly disregard this email. Best regards， Your IECMA 2024 Organizing Team iecma2024(a)mdpi.com

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CWI-SC seminar Beatriz Moya
by Wouter Edeling 21 May '24

21 May '24

Dear all, On May 27 at 11h CET, Beatriz Moya from CNRS@CREATE will speak in our seminar for machine learning and UQ in scientific computing. She will talk about geometric deep learning for model order reduction, see the abstract below. For those at CWI, the location will be L120, and for online attendees the zoom link is posted below. Kind regards, Wouter Edeling 27 May 2024 11h00 CET: Beatriz Moya (CNRS@CREATE) Exploring the role of geometric and learning biases in Model Order Reduction and Data-Driven simulation This talk highlights the practical application and synergistic use of geometric and learning biases in interpretable and consistent deep learning for complex problems. We propose the use of Geometric Deep Learning for Model Order Reduction. Its high generalizability, even with limited data, facilitates real-time evaluation of partial differential equations (PDEs) for complex behaviors and changing domains. Additionally, we showcase the application of Thermodynamics-Informed Machine Learning as an alternative when the physics of the system under study is not fully known. This algorithm results in a cognitive digital twin capable of self-correction for adapting to changing environments when only partial evaluations of the dynamical state are available. Finally, the integration of Geometric Deep Learning and Thermodynamics-Informed Machine Learning produces an enhanced combined effect with high applicability in real-world domains. Join Zoom Meeting https://cwi-nl.zoom.us/j/84808038602?pwd=K3VuMHZvZmI4L0U0ckJrYUlrUmNSZz09 Meeting ID: 848 0803 8602 Passcode: 469712

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BeNeRL Reinforcement Learning Seminar: Edward Hu from the University of Pennsylvania (May 16, this Thursday)
by Yang, Z. (Zhao) 13 May '24

13 May '24

Dear colleagues, Our next BeNeRL Reinforcement Learning Seminar (May 16) is coming: Speaker: Edward Hu (https://edwardshu.com<https://edwardshu.com/>), PhD student from the University of Pennsylvania. Title: The Sensory Needs of Robot Learners Date: May 16, 16.00-17.00 (CET) Please find full details about the talk below this email and on the website of the seminar series: https://www.<https://www.benerl.org/seminar-series>bene<https://www.benerl.org/seminar-series>rl.org/seminar-series<https://www.benerl.org/seminar-series> The goal of the online BeNeRL seminar series is to invite RL researchers (mostly advanced PhD or early postgraduate) to share their work. In addition, we invite the speakers to briefly share their experience with large-scale deep RL experiments, and their style/approach to get these to work. We would be very glad if you forward this invitation within your group and to other colleagues that would be interested (also outside the BeNeRL region). Hope to see you on May 16! Kind regards, Zhao Yang & Thomas Moerland Leiden University —————————————————————— Upcoming talk: Date: May 16, 16.00-17.00 (CET) Speaker: Edward Hu (https://edwardshu.com<https://edwardshu.com/>) Title: The Sensory Needs of Robot Learners Zoom: https://universiteitleiden.zoom.us/j/65411016557?pwd=MzlqcVhzVzUyZlJKTEE0Nk… Abstract: What information does a robot need from the environment to efficiently learn new behaviors? Sensory streams and policy learning are intimately entangled. From current observation, agents learn models and compute feedback for improvement. Then, agents influence future observations through environmental interaction. I will present our recent findings in investigating the close-knit relationship between sensing and learning for robotics. This talk will cover a model-based RL approach that exploits additional sensors to improve policy search and an RL agent that learns interactive perception behavior to better estimate rewards. Overall, we find that paying careful attention to the sensory input streams of the RL process leads to large gains in performance. Bio: Edward Hu is a PhD student at the University of Pennsylvania and GRASP lab, advised by Dinesh Jayaraman. Edward is broadly interested in artificial intelligence, ranging from virtual agents to physical robots. As a result, his research spans reinforcement learning, perception, and robotics. His research has received multiple distinctions in robotics and machine learning venues like Best Paper Award at CoRL22, and spotlights at ICLR23 and ICLR24.

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Machine-learning-nederland May 2024