Chair of Statistical Learning and Data Science at the LMU Munich
LightNews LightNews
slds-lmu.bsky.social
Chair of Statistical Learning and Data Science at the LMU Munich
@slds-lmu.bsky.social
45 followers 20 following 7 posts
https://www.slds.stat.uni-muenchen.de
Posts Replies Media Videos
slds-lmu.bsky.social
🎉 We're excited to share that our paper “Overtuning in Hyperparameter Optimization” (by Lennart Schneider, Bernd Bischl and @matthiasfeurer.bsky.social ) won the Best Paper Award at the 4th @automl-conf.bsky.social ! 🏆

CC @munichcenterml.bsky.social @lmumuenchen.bsky.social
automl-conf.bsky.social AutoML Conference @automl-conf.bsky.social · Sep 8
Best paper award!!! Congrats to the authors, super deserved! 🏆

Check it out here: arxiv.org/pdf/2506.19540

#AutoML25 #AutoMLconf
September 30, 2025 at 10:31 AM
Reposted by Chair of Statistical Learning and Data Science at the LMU Munich
matthiasfeurer.bsky.social
Check out openml.org and also join the OpenML Slack to learn about latest developments and upcoming workshops: openml.slack.com/join/shared_... 4/4
OpenML
OpenML is an open platform for sharing datasets, algorithms, and experiments - to learn how to learn better, together.
openml.org
July 7, 2025 at 12:15 PM
Reposted by Chair of Statistical Learning and Data Science at the LMU Munich
matthiasfeurer.bsky.social
Joaquin Vanschoren, Jos van der Welde and Marcel Wever. 3/4
July 7, 2025 at 12:15 PM
Reposted by Chair of Statistical Learning and Data Science at the LMU Munich
cp-patterns.bsky.social
Online Now: OpenML: Insights from 10 years and more than a thousand papers #datascience
OpenML: Insights from 10 years and more than a thousand papers
The authors reflect on 10 years of OpenML, the open-source platform that turns machine-learning experiments into open, linked, and reusable knowledge. They present the current state of the OpenML ecosystem and its design and assess how community-curated datasets, tasks, and benchmark suites have powered more than 1,500 studies, advanced machine-learning research, and improved reproducibility. Lastly, they share lessons from a decade of building, maintaining, and expanding OpenML to guide the future of open-science infrastructure for machine learning.
dlvr.it
July 3, 2025 at 3:36 PM
Reposted by Chair of Statistical Learning and Data Science at the LMU Munich
matthiasfeurer.bsky.social
with @slds-lmu.bsky.social, @giuseppe88.bsky.social, @tan-iya.bsky.social, myself, Sebastian Fischer, Pieter Gijsbers, Subhaditya Mukherjee, Andreas C. Müller, László Németh, @luisoala.bsky.social, @lennartpurucker.bsky.social, @sahithya.bsky.social, Jan N. van Rijn, @prabhant.bsky.social 2/4
July 7, 2025 at 12:15 PM
slds-lmu.bsky.social
Last week, @assenmacher.bsky.social (Postdoc at SLDS; leading the NLP focus group) received the Teaching Award for Junior Lecturers 2025 from the Business Administration Student Council WASTI. Great to see that the effort we as a chair put into teaching is rewarded in such a nice way 🙂
July 4, 2025 at 6:37 AM
Reposted by Chair of Statistical Learning and Data Science at the LMU Munich
janetlauyeung.bsky.social
🛎️ Excited to announce the 1st Workshop on Bridging NLP and Public Opinion Research at COLM 2025, Oct 10th in Montreal 🇨🇦

As LLMs reshape public discourse and research, collaboration between NLP and Public Opinion Research (POR) is more vital than ever #NLPOR Submit by June 23📄

🔗 tinyurl.com/nlpor25
Welcome to the First Workshop on Bridging NLP and Public Opinion Research, co-located with COLM 2025, October 10, 2025, Montreal, Canada.
May 16, 2025 at 1:24 PM
slds-lmu.bsky.social
Feature importance measures can clarify or mislead. PFI, LOCO, and SAGE each answer a different question.
Understand how to pick the right tool and avoid spurious conclusions: mcml.ai/news/2025-03...
@fionaewald.bsky.social @ludwig-bothmann.bsky.social @giuseppe88.bsky.social @gunnark.bsky.social
mcml.ai
May 12, 2025 at 12:54 PM
slds-lmu.bsky.social
Join Lennart Schneider tomorrow for a presentation of our recent #NeurIPS publication "Reshuffling Resampling Splits Can Improve Generalization of Hyperparameter Optimization" at the #AutoML seminar at 3PM CET.

Link: automl-seminars.github.io
Paper: proceedings.neurips.cc/paper_files/...
AutoML Seminar
Website for the AutoML seminars
automl-seminars.github.io
February 26, 2025 at 4:38 PM
Reposted by Chair of Statistical Learning and Data Science at the LMU Munich
giuseppe88.bsky.social
Excited to share that our #ICLR paper, “Efficient & Accurate Explanation Estimation with Distribution Compression” made the top 5.1% of submissions at #ICLR and was selected as a Spotlight! Congrats to the first author @hbaniecki.com #xAI #interpretableML
February 11, 2025 at 10:23 AM