- Ml-reading-group - lists.saarland-informatics-campus.de

Joint Workshop - October 16th
by kalampalikis 15 Oct '24

15 Oct '24

Dear all, This is just a quick reminder that tomorrow (October 16th), instead of our usual reading group, we will have a joint workshop between our two groups. We’ll start the day with introductions – just a short bit about who you are (name, country, background, and what you’re working on). You can find more details in the program below: === Introduction by everyone: 10:30 - 11:00 Coffee break: 11:00 - 11:20 Isabel & Krikamol talk: 11:20 - 12:00 Lunch: 12:00 - 13:00 Postdocs: 13:00 - 13:30 Coffee break: 13:30 - 14:00 Discussion: 14:30 - 16:00 === Looking forward to seeing you all tomorrow @ CISPA building E1.9. And don't forget to have fun! Best regards, Nektarios Kalampalikis

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Problem with new link
by kalampalikis 02 Oct '24

02 Oct '24

Dear all, There is a problem with the new link. For today, we will be using the old one: https://cs-uni-saarland-de.zoom.us/j/91937148099?pwd=R1BhUVVVMXJKRWU1OXI5al… Nektarios

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Change of Zoom link - Reading Group
by kalampalikis 01 Oct '24

01 Oct '24

Hello everyone, Please note that the Zoom link for the Reading Group has been changed. The new link is: https://cs-uni-saarland-de.zoom.us/j/85631366817?pwd=o3VjvUCoce0lRvJoTCQxpO… . Make sure to use this link for all future meetings. Best regards, Nektarios Kalampalikis

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- Strategic Classification under Unknown Personalized Manipulation - Wednesday, 02.10.2024, 14:30
by Huynh Quang Kiet Vo 30 Sep '24

30 Sep '24

Dear all, For this week's reading group on Wednesday, I will present the paper Strategic Classification under Unknown Personalized Manipulation. The session will take place at 14:30 (on Wednesday) in CISPA's D2 building, room 1.16 and via the usual Zoom link, which you can find from the google sheet. We look forward to your participation. Best Regards, Kiet Vo

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RG September 4th - Fairness Beyond Binary Decisions: A Causal Framework to Measure Treatment Discrimination
by kalampalikis 02 Sep '24

02 Sep '24

Dear all, I hope this email finds you well. For the next reading group (Wednesday, September 4th) we will have *Deborah* presenting a recent work by her, Ayan, Kavya and Prof. Isabel, called "Fairness Beyond Binary Decisions: A Causal Framework to Measure Treatment Discrimination". As always, the reading group will take place from *14:30* to max 16:00. For those physically in the UdS campus, the session will be hosted as usual in *room 0.01 of the E.1.7 building*. For those attending remotely, we will set up the Zoom session for which you can find a link in the google sheet. Please let me know if I missed something. Otherwise, I'll see you soon! Cheers, Nektarios

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[Cancelled RG] Presenter is Unwell
by kalampalikis＠cs.uni-saarland.de 20 Aug '24

20 Aug '24

Dear all, I hope this email finds you well. Unfortunately, I need to inform you that tomorrow's (21/08/2024) presentation on "Differentiable Pattern Set Mining" is cancelled, since Tim, has tested positive for COVID-19. Thank you for your understanding and see you on 04/09/2024. Best regards, Nektarios Kalampalikis

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- Regressception: Exploiting Variances in Regression Coefficients for Discovering Causality and Confounding
by Huynh Quang Kiet Vo 05 Aug '24

05 Aug '24

Dear all, For this week's reading group, Ahmed will present his master's thesis titled Regressception and discuss his approach in using regression for causal discovery under hidden confounding. The session will take place at 14:30, on Wednesday, and _virtually_. Please use the usual Zoom link for this session, which can also be found in the Google Sheet, or below: * https://cs-uni-saarland-de.zoom.us/j/91937148099?pwd=R1BhUVVVMXJKRWU1OXI5al… We look forward to your participation. Best Regards, Kiet Vo

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- Bayes correlated equilibrium and the comparison of information structures in games
by Huynh Quang Kiet Vo 08 Jul '24

08 Jul '24

Dear all, For this week's reading group on Wednesday, I will present the paper Bayes correlated equilibrium and the comparison of information structures in games, and maybe discuss about its connection to causal learning. The session will take place at 14:30 in CISPA's D2 building, room 1.16 and via the usual Zoom link, which you can find from the google sheet. We look forward to your participation. Best Regards, Kiet Vo

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Tomorrow Wed - Alejandro Almódovar - Deriving Causal Order from Single-Variable Interventions: Guarantees & Algorithm
by Adrián Javaloy 25 Jun '24

25 Jun '24

Dear ML reading group, For tomorrow's reading group we will have *Alejando Almódovar*, who is visiting our lab during the summer, presenting an interesting paper in causal discovery that came out recently titled Deriving Causal Order from Single-Variable Interventions: Guarantees & Algorithm <https://arxiv.org/abs/2405.18314>. As always, the reading group will take place from *14:30* to max 16:00. For those physically in the UdS campus, the session will be hosted as usual in *room 0.01 of the E.1.7 building*. For those attending remotely, we will set up the Zoom session for which you can find a link in the google sheet . Please let me know if I missed something. Otherwise, I'll see you tomorrow! Cheers, Adrián

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Imprecise Probabilistic Machine Learning - Wednesday, June 12th @ 2pm
by Huynh Quang Kiet Vo 12 Jun '24

12 Jun '24

Dear all, This Wednesday (June 12th), we combine the Reading Group session with a research talk at CISPA, by Dr. Michele Caprio (University of Manchester), at 2pm (that is, _30 minutes earlier_ than usual). Everyone is cordially invited to attend. The session will be hosted by Siu-Lun (Alan) Chau, your usual reading group master from CISPA side. Title: Imprecise Probabilistic Machine Learning: Being Precise about Imprecision Location: on Zoom [link [1]]. We also plan to book a room at CISPA's D2 building for colleagues who wish to participate together, the detail will be updated in the spreadsheet [link [2]] later. Talk Abstract: This talk is divided into two parts. I will first introduce the field of "Imprecise Probabilistic Machine Learning", from its inception to modern-day research and open problems, including motivations and clarifying examples. In the second part, I will present some recent results that I've derived together with colleagues at Oxford Brookes on Credal Learning Theory. Statistical Learning Theory is the foundation of machine learning, providing theoretical bounds for the risk of models learned from a (single) training set, assumed to issue from an unknown probability distribution. In actual deployment, however, the data distribution may (and often does) vary, causing domain adaptation/generalization issues. We laid the foundations for a credal theory of learning, using convex sets of probabilities (credal sets) to model the variability in the data-generating distribution. Such credal sets, we argued, may be inferred from a finite sample of training sets. We derived bounds for the case of finite hypotheses spaces (both assuming realizability or not), as well as infinite model spaces, which directly generalize classical results. This talk is based on the following work, https://doi.org/10.48550/arXiv.2402.00957. Bio: Michele is a Lecturer (Assistant Professor) in Machine Learning and Artificial Intelligence at The University of Manchester. He obtained his PhD in Statistics from Duke University, and worked as a postdoctoral researcher in the Department of Computer and Information Science of the University of Pennsylvania. His general interest is probabilistic machine learning, and in particular the use of imprecise probabilistic techniques to investigate the theory and methodology of uncertainty quantification in Machine Learning and Artificial Intelligence. Recently, he won the IJAR Young Researcher and the IMS New Researcher Awards, and he was elected member of the London Mathematical Society. We look forward to your participation. Best Regards, Kiet Vo Links: ------ [1] https://cispa-de.zoom-x.de/my/muandet [2] https://docs.google.com/spreadsheets/d/1vtgEezBqS4d_ACPt-emK2NT52x7nofX9jxg…

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