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The #AI Symposium with pitch talks of the new #AI & #DataScience professors at Universität München was a great success. We also felt very honored by the greetings of Vice-President Jahraus, Ministerialdirigent Greiner, and the head of baiosphere Michael Klimke. Research in Bavaria

Passionate about diving into the world of Interpretable Machine Learning and Explainable AI for a PhD at Universität München? Apply now! 🎓 Explainable AI #PhD #XAI #MachineLearning #Statistics #ExplainableAI #DataScience #InterpretableML job-portal.lmu.de/jobposting/09f…

Excited to say that 'Applied #MachineLearning Using #mlr3 in #RStats' has gone to press and will be published by CRC Press Data Science, Stats, and Math Books in January. Pre-order from Amazon. amazon.co.uk/Applied-Machin… SLDS / Bernd Bischl Lars Kotthoff ❎ @michellangts #DataScience #Statistics

Our paper “Probabilistic Self-supervised Representation Learning via Scoring Rules Minimization” with Amirhosein Vahidi , Simon Schosser, Lisa Wimmer ,yawei.li.the_unique ,SLDS / Bernd Bischl , and Eyke Hüllermeier from Universität München has been accepted at #ICLR_2024. Preprint 📚: arxiv.org/pdf/2309.02048…

2023 featured article of TELO "Multi-Objective Hyperparameter Optimization," provides an extensive survey of hyperparameter optimization that covers the domains of evolutionary algorithms. TELO@ACM Tobias Pielok @FlorianPfi Jakob Richter @michellangts SLDS / Bernd Bischl bit.ly/3SEDUo9

📢 The #DDSG-Team is searching for project partners for this year's 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗳𝗼𝗿 𝗦𝗼𝗰𝗶𝗮𝗹 𝗚𝗼𝗼𝗱 𝟮𝟬𝟮𝟰. You will work with a team of 4-5 Fellows led by experienced mentors to solve a problem for the social good. ➡ dssgxmunich.org/call-for-proje…

Ihr möchtet alles über #MachineLearning erfahren? Die 3 Kurse aus der englischsprachigen Reihe "Introduction to Machine Learning" von der Universität München & dem Munich Center for Machine Learning sind jetzt online! 🤖 Hier starten: ➡️ki-campus.org/courses/I2ML_P… #KICampus #KI #MachineLearning #ML

📢 Are you aware that most of the commonly used datasets used in Tabular Deep Learning are more than 10 years old? If you want to learn more interesting facts about datasets used in Tabular DL, check out our poster at the Journal of Data-centric Machine Learning Research workshop ICLR 2026 . 1/3

Wondering how humans should be involved in designing #AutoML solutions 🤔? Check out our #ICML2024 paper: "Position: A Call to Action for a Human-Centered AutoML Paradigm"! 📄✨ proceedings.mlr.press/v235/lindauer2… Drop by at our poster on Thu, Jul 25 at 11:30 AM in Hall C 4-9 #2003 📅 1/3

What makes AI research excellent? Who are the researchers behind MCML? And what drives us at MCML? Get to know us in our imagefilm⬇️ youtube.com/watch?v=o0IRB2…

We are looking for a PhD in Interpretable Machine Learning and Explainable AI Universität München. Apply now at join.com/companies/uni-…! Explainable AI #PhD #XAI #MachineLearning #Statistics #ExplainableAI #DataScience #InterpretableML

We have another opening for a PhD in AutoML Universität München. Apply now at job-portal.lmu.de/jobposting/ba1… #PhD #MachineLearning #Statistics #DataScience #AutoML

The #MCML offers fully funded #PhD positions in any field of research within the domains of machine learning! The Online Application System is open from 15 October 2024 until 14 November 2024! The position starts on 1 July 2025 Further information: mcml.ai/opportunities/…

Our paper: **A Dual-Perspective Approach to Evaluating Feature Attribution Methods** with yawei.li.the_unique Yang Zhang, Kenji Kawaguchi, Ashkan Khakzar, SLDS / Bernd Bischl , Mina Rezaei from Munich Center for Machine Learning has been accepted at TMLR

The #mlr3 book has a new chapter on validation / internal tuning / early stopping: mlr3book.mlr-org.com/chapters/chapt… Covers: validation splits for iterative learners such as XGB or NNs, works even in pipelines and can easily be combined with tuning #RStats #mlr3 #DataScience #Statistics

MCML has 26 papers at NeurIPS 2024: mcml.ai/news/2024-12-0… #MCML #LMU #TUM

🚀 Our paper proposing a new paradigm for more efficient estimation of machine learning explanations is accepted at #ICLR2025! This is joint work with Giuseppe Casalicchio, SLDS / Bernd Bischl & Przemysław Biecek, to be presented in Singapore 🇸🇬 👇1/5

Our #ICLR paper, “Efficient & Accurate Explanation Estimation with Distribution Compression” made the top 5.1% of submissions and was selected as a Spotlight! Congrats to the first author Hubert Baniecki #xAI #interpretableML Paper: arxiv.org/abs/2406.18334