October 2024 - Machine-learning-nederland

Register now: AIM PhD networking event (21 November 2024)
by Tim van Erven 31 Oct '24

31 Oct '24

Dear all, On 21 November 2024, 13:00 - 17:30, AIM is hosting a PhD networking event at CWI. Advisors, please 'encourage' interested PhD students to present. The meeting is intended for PhD students working on mathematical research in AI to present their work. Everyone is welcome to attend. Please register via the registration form on the AIM website <https://aimath.nl/index.php/2024/10/04/852/>. *Preliminary program:* 1. 13:00 - 13:30: Walk-in with coffee/tea 2. 13:30 - 14:30: Opening and keynote presentation by Meike Nauta (Datacation) 3. 14:30 - 15:00: Coffee break 4. 15:00 - 17:00: Presentations and poster session 5. From 17:00: Drinks & networking *Call for presentations:* Interested PhD students who would like to present their research at the community event can register via the registration form. The deadline is Tuesday, 12 November 2024. Shortly after the deadline, applicants will be informed whether they can present their work at the event. Please share this call for presentations with any interested PhD candidates. If you have any questions, please contact us via aim(a)nwo.nl. *Key note presentation: Meike Nauta - Making Impact with AI in Practice* Meike Nauta will tell about her step from academia to industry, and how she uses the knowledge from her PhD for real-life AI applications in the Netherlands. Meike Nauta has a cum laude PhD in Explainable AI from the University of Twente (May 2023). She is currently working as a senior data scientist and AI consultant at Datacation. ---- Save the Date - UNRAVEL workshop (17 December 2024) On 17 December 2024, the Gravitation project UNRAVEL will organize a workshop at TU Eindhoven's "Black Box". AIM will contribute to the organization of the workshop. Further announcements and more information about the event will follow. ---- Tim (on behalf of AIM) -- Tim van Erven<tim(a)timvanerven.nl> www.timvanerven.nl

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Let-All's 7th Mentorship Workshop, Nov 13
by Tim van Erven 31 Oct '24

31 Oct '24

Forwarding on behalf of Ciara Pike-Burke: This is about an online mentorship workshop where PhD students and postdocs can get advice on how to organize research from a star cast of international learning theory researchers. Highly recommended! Tim -------- Forwarded Message -------- We are pleased to invite you to the 7th Learning Theory Alliance Mentorship workshop <https://let-all.com/fall24.html>, to be held on November 13, 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. No prior research experience in the field is expected. The theme of our event is /diversity in research approaches. /We have several planned events including: * Two sessions (morning ET and evening ET) of moderated discussions on: 1) Different types of learning theory research, 2) “Fast” and “slow” approaches to research, and 3) Individual and collaborative approaches to research. Each discussion will involve two learning theory research experts. * A social hour with mentoring tables. Our lineup includes: Shipra Agrawal (Columbia), Kamalika Chaudhuri (UCSD), Nicolas Flammarion (EPFL), Tor Lattimore (DeepMind), Gergely Neu (UPF-Barcelona), Ariel Procaccia (Harvard), Aaron Roth (UPenn), Jonathan Scarlett (NUS), Tselil Schramm (Stanford), Aaron Sidford (Stanford), Christina Lee Yu (Cornell) and Angela Zhou (USC). A short registration form <https://docs.google.com/forms/d/e/1FAIpQLSf9cT3ux3wCC0WzSIrwqgjFI_R1yALUmOF…> is required to participate with a deadline of *November 8, 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/fall24.html <https://let-all.com/fall24.html>. This workshop is part of our broader community-building initiative called the Learning Theory Alliance (founded by Surbhi Goel, Nika Haghtalab, and Ellen Vitercik; advised by Peter Bartlett, Avrim Blum, Stefanie Jegelka, Po-Ling Loh, and Jenn Wortman Vaughan). Check out<http://let-all.com/>http://let-all.com/ for more details. To connect with fellow participants and stay in touch for more announcements, we encourage everyone to<https://join.slack.com/t/learningtheor-cui5258/shared_invite/zt-2421d3wfl-o…>join <https://join.slack.com/t/learningtheor-cui5258/shared_invite/zt-2421d3wfl-o…> the LeT-All slack. Best, Ciara Pike-Burke, Thodoris Lykouris, Tijana Zrnic and Vidya Muthukumar LeT-All’s Mentoring Workshop Committee

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Stats and ML Thematic seminar: Julien Zhou, Monday October 21, 16h00
by Tim van Erven 18 Oct '24

18 Oct '24

Dear all, This Monday, October 21, we have Julien Zhou speaking in the Statistics and Machine Learning Thematic Seminar. Julien is a visiting PhD student from Inria and Criteo. *Julien Zhou *(Inria Grenoble-Alpes and Criteo AI Lab, https://jlnzhou.github.io/) *Monday October 21*, 16h00-17h00 Hybrid, at the University of Amsterdam and Online Location: Korteweg-de Vries Institute for Mathematics, Science Park 907, Room F1.15 Directions: https://kdvi.uva.nl/contact/contact.html Online: https://uva-live.zoom.us/j/83485037604 *Submodular Optimization with Bandit feedbacks *We address the online unconstrained submodular maximization problem (Online USM), in a setting with stochastic bandit feedback. In this framework, a decision-maker receives noisy rewards from a nonmonotone submodular function, taking values in a known bounded interval. We propose an Explore-then-Commit inspired approach satisfying logarithmic problem-dependent, 1/2-approximate regret, leveraging the inner structure of the reward. Seminar organizers: Tim van Erven https://mschauer.github.io/StructuresSeminar/ -- Tim van Erven<tim(a)timvanerven.nl> www.timvanerven.nl

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Two PhD positions in Reinforcement Learning for Sustainable Energy @ Leiden University
by Moerland, T.M. (Thomas) 17 Oct '24

17 Oct '24

Dear colleagues, We have two PhD vacancies in reinforcement learning for sustainable energy at Leiden University: https://www.universiteitleiden.nl/vacatures/2024/q4/15143-2-phd-candidates-… Should you know suitable candidates, then we're grateful if you forward the vacancy! Kind regards, Thomas Moerland

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Reminder: AIM matchmaking for collaborative research grants on October 24
by Tim van Erven 09 Oct '24

09 Oct '24

Dear all, This is a reminder for the upcoming AI & Mathematics matching event. Registrations: here <https://nl.surveymonkey.com/r/G3XVCXG> by *October 15*. To pitch a research idea for potential collaborations: mail the AIM board (aim(a)nwo.nl) before *October 11*. The AIM Board cordially invites you to attend the AIM Matchmaking Session on 24 October 2024 at Winthonlaan 2, 3526 KV Utrecht (NWO building). The goal of the workshop is to facilitate the formation of potential new research collaborations between mathematicians working on AI-related topics, serving the overarching ambition of forming consortia for large and medium-sized collaborative research grants (e.g. Open Competition ENW-M2, NWO’s Open Competition XL [expected deadline pre-proposals September 2025] or “Zwaartekracht”). Should you wish to attend, please register here <https://nl.surveymonkey.com/r/G3XVCXG> by 15 October 2024. In case you have a clear central research idea to pitch for a potential collaborative application, please send an email to the AIM board (aim(a)nwo.nl) including your research idea before 11 October 2024. AIM will inform you on 15 October 2024 about the acceptance of the pitches. During the workshop, you will then have time to present your research idea (time depending on number of pitches, you will informed in advance). Please note: if not all pitches can be presented due to time-constrains, alternatives to share the research ideas will be provided. /Programme (see a more detailed version on the website <https://aimath.nl/index.php/2024/09/23/824/>)/ The matchmaking will start at 10:00 on 24 October 2024. After a short welcome by the AIM board, researchers will have the chance to pitch their research ideas. During various sessions, discussion and consortium-building will be facilitated. Additionally, the program will include a panel discussion with researchers that have already successfully secured a collaborative research grant. We hope that this program will inspire and encourage our community to come up with new and exciting scientific ideas and impactful research proposals! We hope to meet many of you there, The AIM board Christoph Brune Tim van Erven Tristan van Leeuwen Leo van Iersel -- Tim van Erven<tim(a)timvanerven.nl> www.timvanerven.nl

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fully funded PhD position at MIDS (Germany)
by Salanevich, P. (Palina) 08 Oct '24

08 Oct '24

Dear colleagues, Please, see information about a fully funded PhD position opportunity at the Mathematical Institute for Machine Learning and Data Science (https://www.ku.de/mids), KU Eichstätt-Ingolstadt. Feel free to forward the information to anyone who may be interested. Thank you! Best wishes, Palina Prof. Tijana Janjic, Heisenberg professor for data assimilation within the Mathematical Institute for Machine Learning and Data Science (https://www.ku.de/mids) at KU Eichstätt Ingolstadt invites applications for a PhD student (m/f/d) position at the next possible starting date. The contract duration will be 3 years. The place of work shall be Ingolstadt, Germany. Renumeration will be according to appropriate E13 TV-L pay grade. The successful candidate will work on the project entitled “Uncertainty-aware and physics-informed machine learning for short range atmospheric forecasts” funded by Klaus Tschira Foundation. This is a twin project, jointly with group of Prof. Hüllermeier, LMU, Munich, Germany. The main goal of the project is to develop machine learning methodology specifically tailored to the task of forecasting and uncertainty quantification on the convective scales. Your profile - MSc in physics, mathematics or meteorology, - Programming skills - Ability to work in a team - Ability to structure and pursue a successful research agenda on cutting edge topics - Flexibility and willingness to travel Knowledge/experience with data assimilation or machine learning is beneficial but not required. German language skills are not required. Your application Please send your application with the usual supporting documents by e-mail to Prof. Dr. Tijana Janjic (tijana.janjic(a)ku.de<mailto:tijana.janjic@ku.de>) by October 15th, 2024 (please combine all documents in one PDF file). Your documents should include cover letter, curriculum vitae and copies of transcripts and degree certificates. Applicants’ documents will be deleted after completion of the recruitment process in compliance with data protection regulations. -- Palina Salanevich, Assistant Professor, Mathematical Institute, Utrecht University https://www.uu.nl/staff/PSalanevich (she/her/hers)

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fully funded PhD position at MIDS (Germany)
by Salanevich, P. (Palina) 08 Oct '24

08 Oct '24

Dear Master’s students, colleagues, Please, see information about a fully funded PhD position opportunity at the Mathematical Institute for Machine Learning and Data Science (https://www.ku.de/mids), KU Eichstätt-Ingolstadt. Feel free to forward the information to anyone who may be interested. Thank you! Best wishes, Palina Prof. Tijana Janjic, Heisenberg professor for data assimilation within the Mathematical Institute for Machine Learning and Data Science (https://www.ku.de/mids) at KU Eichstätt Ingolstadt invites applications for a PhD student (m/f/d) position at the next possible starting date. The contract duration will be 3 years. The place of work shall be Ingolstadt, Germany. Renumeration will be according to appropriate E13 TV-L pay grade. The successful candidate will work on the project entitled “Uncertainty-aware and physics-informed machine learning for short range atmospheric forecasts” funded by Klaus Tschira Foundation. This is a twin project, jointly with group of Prof. Hüllermeier, LMU, Munich, Germany. The main goal of the project is to develop machine learning methodology specifically tailored to the task of forecasting and uncertainty quantification on the convective scales. Your profile - MSc in physics, mathematics or meteorology, - Programming skills - Ability to work in a team - Ability to structure and pursue a successful research agenda on cutting edge topics - Flexibility and willingness to travel Knowledge/experience with data assimilation or machine learning is beneficial but not required. German language skills are not required. Your application Please send your application with the usual supporting documents by e-mail to Prof. Dr. Tijana Janjic (tijana.janjic(a)ku.de<mailto:tijana.janjic@ku.de>) by October 15th, 2024 (please combine all documents in one PDF file). Your documents should include cover letter, curriculum vitae and copies of transcripts and degree certificates. Applicants’ documents will be deleted after completion of the recruitment process in compliance with data protection regulations. -- Palina Salanevich, Assistant Professor, Mathematical Institute, Utrecht University https://www.uu.nl/staff/PSalanevich (she/her/hers)

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BeNeRL Reinforcement Learning Seminar: Ademi Adeniji from UC Berkley (October 10, this Thursday)
by Yang, Z. (Zhao) 08 Oct '24

08 Oct '24

Dear colleagues, Our next BeNeRL Reinforcement Learning Seminar (Oct. 10) is coming: Speaker: Ademi Adeniji (https://ademiadeniji.github.io<https://ademiadeniji.github.io/>), PhD student from UC Berkeley. Title: Reinforcement Learning Behavioral Generalists - Top-Down and Bottom-Up Date: October 10, 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.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 October 10! Kind regards, Zhao Yang & Thomas Moerland VU Amsterdam & Leiden University —————————————————————— Upcoming talk: Date: October 10, 16.00-17.00 (CET) Speaker: Ademi Adeniji (https://ademiadeniji.github.io<https://ademiadeniji.github.io/>) Title: Reinforcement Learning Behavioral Generalists - Top-Down and Bottom-Up Zoom: https://universiteitleiden.zoom.us/j/65411016557?pwd=MzlqcVhzVzUyZlJKTEE0Nk… Abstract: The success of training large foundation models with scalable, self-supervised objectives has led to significant advancements in AI, particularly in vision and language. In this talk, I argue that while many challenges in general-purpose agentic learning can be mitigated by using these models as black boxes, there remain valuable opportunities for scalable pretraining tailored specifically to the reinforcement learning domain. I will present work from both perspectives: first, showcasing how foundation models trained via conventional methods can enhance decision-making, and second, exploring novel, scalable pretraining approaches that are native to control and hold promise for endowing artificial agents with stronger forms of behavioral generalization. Bio: Ademi Adeniji is a Computer Science PhD student at UC Berkeley advised by Pieter Abbeel. Ademi’s research interests lie in creating agents capable of developing general-purpose intelligent behaviors through data and experience. To this end, his work has focused on self-supervised reinforcement learning algorithms for enabling agents to discover broad control strategies without human supervision for efficiently solving new and unseen tasks. He previously interned at NVIDIA where he worked on reinforcement learning and robotics. He completed his BS and MS at Stanford University conducting research in the Stanford Vision and Learning Lab advised by Fei-Fei Li. He is supported by the Berkeley Chancellors Fellowship.

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Machine-learning-nederland October 2024