- Machine-learning-nederland

June 21, 15:00 Machine Learning Theory Seminar++ Meeting with Alexander Ly
by Wouter Koolen-Wijkstra 17 Jun '23

17 Jun '23

Dear researchers, Centrum Wiskunde & Informatica (CWI) kindly invites you to the eight Seminar++ meeting on Machine Learning Theory, taking place on Wednesday June 21 from 15:00 - 17:00. These Seminar++ meetings consist of a one-hour lecture building up to an open problem, followed by an hour of brainstorming time. The meeting is intended for interested researchers including PhD students. These meetings are freely accessible without registration. Cookies, coffee and tea will be provided in the half-time break. The meeting of 21 June will be hosted by: Alexander Ly <https://www.alexander-ly.com/>, Postdoc at the Centrum Wiskunde & Informatica <https://www.cwi.nl/>. On constructing e-values for statistical practice *Abstract:* The safe anytime-valid inference framework based on e-values allows practitioners to adaptively design their experiments and draw more reliable conclusions compared to conventional p-value-based approaches. The presentation begins with a concise overview of the recently developed general theory of e-values and the various procedures to construct them. In order to distinguish among the different e-values, Grünwald, de Heide and Koolen (2019) introduced the GROW criterion along with a general procedure specifically designed to construct the optimal e-value according to this criterion. Practical considerations and the context of the statistical problem itself might lead us to deviate from recommending this so-called GROW e-value. We shed light on the choices we made when constructing e-values for fundamental classical inference problems, such as z-tests, t-tests, one-way ANOVAs, and (generalised) linear models. Our objective is to investigate the potential generalisability of these context-specific solutions to a broader range of inference problems in hope to expand the practicality and versatility of safe anytime-valid inference. The event takes place in room L016 in the CWI building, Science Park 123, Amsterdam. The Seminar++ Meetings are part of the Machine Learning Theory Semester Programme <https://www.cwi.nl/en/events/cwi-research-semester-programs/research-progra…>, which runs in Spring 2023. Best regards on behalf of CWI from the program committee, Wouter Koolen

1 0

CfP 7th Interactive Adaptive Learning Workshop @ ECML PKDD 2023 (September, Torino)
by Krempl, G.M. (Georg) 06 Jun '23

06 Jun '23

We organize the 7th international workshop on Interactive Adaptive Learning, to be held at ECML PKDD 2023 on September 22nd in Torino, Italy: Interactive Adaptive Learning Workshop @ ECML PKDD link : https://www.activeml.net/ial2023/ Key dates (Anytime-on-Earth): Abstract Registration: Monday, June 12th 2023 Paper Submission: Wednesday, June 21st 2023 Notification: Monday, July 24th 2023 Camera Ready: Sunday, August 13th 2023 Workshop & Tutorial: Friday, September 22nd, 2021, Torino, Italy Topics of interest include: Novel Techniques for Active, Semi-Supervised, Transfer, or Weakly Supervised Learning Innovative Use and Applications of Active, Semi-Supervised, Transfer, or Weakly Supervised Learning Techniques for Combined Interactive Adaptive Learning We welcome submissions of original regular (8-16 pages) and short papers/extended abstracts (2-4 pages). Each submission will be double-blind peer-reviewed; accepted papers will be published at ceur-ws.org, which is indexed, e.g., by Google Scholar, DBLP, Scopus, and will be presented & discussed at the workshop. For short papers, works-in-progress, open challenges in research or industrial applications that initiate discussions and collaborations are welcome. Please format your papers according to the CEUR-WS format and submit them via EasyChair: https://easychair.org/conferences/?conf=ial2023 We look forward to your contributions and participation at the workshop, the organisers, Mirko Bunse, Barbara Hammer, Georg Krempl, Vincent Lemaire, Alaa Othman, and Amal Saadallah.

1 0

Stats and ML Thematic seminar: Nikita Zhivotovskiy, Friday July 7, 15h00
by Tim van Erven 05 Jun '23

05 Jun '23

Dear all, On Friday July 7 we have Nikita Zhivotovskiy speaking in the Statistics and Machine Learning Thematic Seminar. Nikita will be visiting us July 3-7. He has done excellent work both in statistics and machine learning, so it is highly recommended to come meet him. *Nikita Zhivotovskiy *(UC Berkeley, Department of Statistics, https://sites.google.com/view/nikitazhivotovskiy/) *Friday July 7*, 15h00-16h00 In person, at the University of Amsterdam Location: Science Park 904, Room TBA *Sharper Risk Bounds for Statistical Aggregation *In this talk, we take a fresh look at the classical results in the theory of statistical aggregation, focusing on the transition from global complexity to a more manageable local one. The goal of aggregation is to combine several base predictors to achieve a prediction nearly as accurate as the best one. This flexible approach operates without any assumptions on the structure of the class or the nature of the target. Though aggregation is studied in both sequential and statistical settings, each with their unique differences, they both traditionally use the same "global" complexity measure. Our discussion will highlight the lesser-known PAC-Bayes localization method used in our proofs, allowing us to prove a localized version of a classical bound for the exponential weights estimator by Leung and Barron, and a deviation-optimal localized bound for the Q-aggregation estimator. Furthermore, we will explore the links between our work and ridge regression. Joint work with Jaouad Mourtada and Tomas Vaškevičius. * * Seminar organizers: Tim van Erven Botond Szabo https://mschauer.github.io/StructuresSeminar/ -- Tim van Erven<tim(a)timvanerven.nl> www.timvanerven.nl

1 0

June 7, 15:00 Machine Learning Theory Seminar++ Meeting with Odysseas Kanavetas
by Wouter Koolen-Wijkstra 31 May '23

31 May '23

Dear researchers, Centrum Wiskunde & Informatica (CWI) kindly invites you seventh Seminar++ meeting on Machine Learning Theory, taking place on Wednesday June 7 from 15:00 - 17:00. These Seminar++ meetings consist of a one-hour lecture building up to an open problem, followed by an hour of brainstorming time. The meeting is intended for interested researchers including PhD students. These meetings are freely accessible without registration. Cookies, coffee and tea will be provided in the half-time break. The meeting of 7 June will be hosted by: Odysseas Kanavetas <https://www.universiteitleiden.nl/en/staffmembers/odysseas-kanavetas#tab-1> Assistant Professsor at the University of Leiden <https://www.universiteitleiden.nl/en>. Asymptotically optimal control for Markov Decision Processes (MDP) under side constraints *Abstract:* After a brief review of the multi-armed bandit (MAB) problem and its online machine learning applications, we present our work on the model with side constraints. The constraints represent circumstances in which bandit activations are restricted by the availability of certain resources that are replenished at a constant rate. Then, we consider the problem of adaptive control for Markov Decision Processes (MDP), under side constraints, when there is incomplete information for the transition probabilities and its rewards. Under suitable irreducibility assumptions for the MDP we establish a lower bound for the regret. An open problem is to construct adaptive policies that maximize the rate of convergence of realized rewards to that of the optimal (non adaptive) policy under complete information. We also discuss applications for queuing control problems and reliability models. The event takes place in room L016 in the CWI building, Science Park 123, Amsterdam. The Seminar++ Meetings are part of the Machine Learning Theory Semester Programme <https://www.cwi.nl/en/events/cwi-research-semester-programs/research-progra…>, which runs in Spring 2023. Best regards on behalf of CWI from the program committee, Wouter Koolen

1 0

Two PhD vacancies in Reinforcement Learning @ Leiden University
by Moerland, T.M. (Thomas) 31 May '23

31 May '23

Dear all, The Leiden Institute of Advanced Computer Science (LIACS) is looking for two PhD candidates in the field of Reinforcement Learning. Should you know interested/suitable candidates, then further details are available from: https://www.universiteitleiden.nl/vacatures/2023/q2/13746-2-phd-candidates-… Best regards, Thomas Moerland T.M. (Thomas) Moerland Assistant Professor Leiden University https://thomasmoerland.nl<http://thomasmoerland.nl/>

1 0

Mailing list configuration issue resolved
by Tim van Erven 22 May '23

22 May '23

Dear all, A message about the list administration: Recently e-mails from the mailing list could not be delivered to some users, whose universities have tightened anti-spam measures (using the DMARC protocol). This issue should have been fully resolved several weeks ago, but users may have been automatically unsubscribed after too many failed delivery attempts. If you know someone who has been automatically unsubscribed, please let them know they can resubscribe to the mailing list, and everything should be fine again. Sorry for the inconvenience. Best regards, Tim (machine learning Nederland mailing list admin) -- Tim van Erven <tim(a)timvanerven.nl> www.timvanerven.nl

1 0

L2RPN Delft 2023 competition
by Delft AI Energy Lab 17 May '23

17 May '23

L2RPN Delft 2023 We are excited to announce the next “Learning to Run a Power Network” (L2RPN) competition is happening in the Netherlands! The L2RPN is a series of competitions designed to train an Artificial Intelligence (AI) agent to operate a power network. The L2RPN Delft 2023 competition offers an exciting and exclusive opportunity for students and researchers only in the Netherlands to test their AI solutions against others in a realistic and challenging environment. Form a team and register now! Develop AI solutions, collaborate with fellow innovators, and win prizes up to €1500! We invite you to visit the competition website<https://codalab.lisn.upsaclay.fr/competitions/12420> and join the kick-off meeting<https://docs.google.com/forms/d/e/1FAIpQLSe9ly0ADSW6_wXgBHH9YAAT_STvlIdsqgP…> to learn more about the competition! Important information: * Register for the competition here: https://codalab.lisn.upsaclay.fr/competitions/12420 * Register for Kick-off meeting here<https://docs.google.com/forms/d/e/1FAIpQLSe9ly0ADSW6_wXgBHH9YAAT_STvlIdsqgP…>: 13:00 7-June-2023, location: D@ta hall, EWI, TU Delft. * Competition starts from 7-June-2023 and ends on 1-September-2023. * Know someone interested? Please forward this email! Please don’t hesitate to contact us if you have any questions. On behalf of L2RPN Delft 2023 team Ali Rajaei PhD student Delft AI Energy Lab TU Delft https://www.tudelft.nl/ai/delft-ai-energy-lab

1 0

May 24, 15:00 Machine Learning Theory Seminar++ Meeting with Sophie Langer
by Wouter Koolen-Wijkstra 16 May '23

16 May '23

Dear researchers, Centrum Wiskunde & Informatica (CWI) kindly invites you sixth Seminar++ meeting on Machine Learning Theory, taking place on Wednesday May 24 from 15:00 - 17:00. These Seminar++ meetings consist of a one-hour lecture building up to an open problem, followed by an hour of brainstorming time. The meeting is intended for interested researchers including PhD students. These meetings are freely accessible without registration. Cookies, coffee and tea will be provided in the half-time break. The meeting of 24 May will be hosted by: Sophie Langer <https://sites.google.com/view/sophielanger/start> Assistant Professsor at the University of Twente <https://www.utwente.nl/en/> *Image classification: A (new) statistical viewpoint* *Abstract:* In this talk we consider a simple supervised classification problem for object recognition on grayscale images. There are two possible perspectives to solve this problem. Firstly, one can interpret object recognition as a high-dimensional classification problem, where every pixel is a variable. The task is then to map these pixel values to the conditional class probabilities or the labels. Increasing the dimension makes the problem considerably harder, leading to slow convergence rates due to the curse of dimensionality. Another perspective is to view images as two-dimensional objects. Increasing the number of pixels leads to higher resolution and therefore better performance is expected for large images. Following the second route, we present a new image deformation model, for which we propose and analyze two different classifiers. The first method estimates the image deformation by support alignment. Under a minimal separation condition, it is shown that perfect classification is possible. The second method fits a CNN to the data. We derive a rate for the misclassification error depending on the sample size and the number of pixels /d^2 /. Both classifiers are empirically compared on images generated from the MNIST handwritten digit database. The event takes place in room L016 in the CWI building, Science Park 123, Amsterdam. The Seminar++ Meetings are part of the Machine Learning Theory Semester Programme <https://www.cwi.nl/en/events/cwi-research-semester-programs/research-progra…>, which runs in Spring 2023. Best regards on behalf of CWI from the program committee, Wouter Koolen

1 0

AIM cluster workshop on 1 & 2 June @Twente - register now!
by AI and Mathematics 04 May '23

04 May '23

Dear all, We would like to draw your attention to the next AIM<https://aimath.nl/> workshop on 1&2 June in Twente. We hope to see many of you there! The AIM team [cid:image001.jpg@01D97E91.0F254A00]Don't miss out on the second AIM cluster workshop, taking place on 1 & 2 June at the University of Twente! Organized in collaboration with the Dutch Mathematics Clusters, this workshop aims to strengthen the synergy between different areas of mathematics in AI and bring together researchers across mathematics. Over the course of two days, thematic sessions will highlight connections between the different clusters and provide opportunities for networking and collaboration. Additionally, there will be a panel discussion featuring experts Karen Aardal (TUD) and Wil Schilders (TU/e). There will also be the opportunity to present posters. If you would like to present a poster, please let us know by sending an email to aim(a)nwo.nl<mailto:aim@nwo.nl>. The four thematic sessions will be on the topics: * Geometric Deep Learning session chairs: Remco Duits (TU/e), Bram Mesland (LEI) * Learned Optimization session chairs: Barbara Franci (UM), Julia Olkhovskaya (VU) * Robust AI session chairs: Tim van Erven (UvA), Sophie Langer (UT) * Scientific Machine Learning chairs: Tristan van Leeuwen (CWI), Christoph Brune (UT) Whether you're a researcher, student, or industry professional, this workshop is a great opportunity to learn about the latest developments in AI and mathematics, and connect with peers and experts in the field. To see the updated list of speakers and register for the workshop, please visit the website.<https://www.utwente.nl/en/eemcs/sacs/aim2023/> We look forward to seeing you there!

1 0

PhD positions on AI-Based Pedestrian Crowd Modeling and Management
by Pires da Silva Castro, Rui 27 Apr '23

27 Apr '23

Dear Colleagues, There are two openings for PhD positions at the Eindhoven University of Technology, part of the recently funded AICrowd project: AI-Based Pedestrian Crowd Modeling and Management. I would appreciate it if you could forward this announcement to any potential candidates. Are you eager to work on a pioneering PhD project at the interface between physics of flowing matter, artificial intelligence, system identification, and statistics? Do you enjoy collaborating with researchers from different fields, and combining dynamical systems modeling, optimization and statistical learning theory? Are you eager to see your work making immediate societal impact? Then one of these positions might be for you. AICrowd project - AI-Based Pedestrian Crowd Modelling and Management vacancies: - AI & System identification for crowd flow modeling: https://jobs.tue.nl/en/vacancy/phd-in-artificial-intelligence-for-quantitat… - Statistics and AI for quantitative crowd dynamics modeling: https://jobs.tue.nl/en/vacancy/phd-in-statistics-and-ai-for-quantitative-cr… With best regards, Rui Castro — Dept. of Mathematics and Computer Science, TU/e http://www.win.tue.nl/~rmcastro | +31 40 247 2499

1 0

2025

2024

2023

2022

2021

2020

Machine-learning-nederland