Running some new experiments on ML energy consumption - comparing software-internal profiling (#CodeCarbon) with external power measuring!⚡ All in line to shed more light on #sustainableAI, as part of @LamarrInstitute's research on resource-aware ML! 🌍
Quite shocking... If people would try to explicitly report their numbers on sustainability and resource usage, such (possibly faulty) estimates would not be necessary. Your work is important and valuable!
First half of @ECMLPKDD is over! 🙌 Thanks for the positive feedback on our paper (with @wever_marcel, @sbuschjaeger and @t_liebig) 😌 My 2nd @LamarrInstitute presentation on #SustainableAI and #TrustworthyAI will be this afternoon (Interp. & Explain. Session) - can't wait! – at Vilnius, Lithuania
Well-arrived in #Vilnius for #ECMLPKDD! 🚀 Today presenting "MetaQuRe: #Metalearning from Model Quality and Resource Consumption" link.springer.com/chapter/10… and tomorrow "Towards More #Sustainable and #Trustworthy Reporting in Machine Learning" link.springer.com/article/10… 👨💻🌍 – at Vilnius, Lithuania
Had lots of good conversations on #resourceaware ML and AI after yesterday's talk and at the poster session 🌱🌎 Thank you for the valuable input and feedback, the full #openaccess paper is available here: dl.acm.org/doi/10.1145/36375…
Hola #Barcelona - ready for #kdd2024 @kdd_news, representing @LamarrInstitute 😎 Tomorrow I will present our work on "Automated Multi-Objective Model Selection for Time Series Forecasting" - the #openaccess article is now also published! 👨💻 dl.acm.org/doi/10.1145/36375…
Just published! 🎞️ youtu.be/utfpJNdpsRc?si=hiVR… Promo video for "Automated Multi-Objective #ModelSelection for #TimeSeriesForecasting", co-authored with my @LamarrInstitute colleague @saadallah_amal, to be presented at this year's Hashtag #KDD24! 😎 Watch and share!
📣 Interviewpartner*innen gesucht 📣
Für eine Studie zur "Nützlichkeit von #KI-Labeling" suchen wir Personen aus Industrie und Wirtschaft, die KI-Produkte entwickeln 👨💻 Mehr Infos: QR-Code scannen oder lamarr.cs.tu-dortmund.de/ml-… besuchen - bitte gerne teilen! 🤝
Raphael Fischer retweeted
Machine Learning advances are only as reliable as their evaluations as the authors of the new #DAMI online-first paper stress: "Towards more sustainable and trustworthy reporting in machine learning" by Raphael Fischer, Thomas Liebig & @KatharinaJutta (link.springer.com/article/10…)#OA
Happy to take further steps towards more #sustainable and #trustworthy reporting in #machinelearning 🌱🌎 Collaborative work with @t_liebig and @KatharinaJutta, as part of @LamarrInstitute - link.springer.com/article/10…
Raphael Fischer retweeted
With that the time of the #Lamarr team in #Pittsburgh concludes. 👋 Today, our delegates are heading off to their final stops of the week in #StLouis, #Philadelphia and #NewYork. 🧳 We are excited to see what great insights & collaborations they will return to Germany with. (3/3)
Final stop at @WUSTL is now over - three cities, five flights, conversations with about 100 people, all within seven days - but I enjoyed every second building international bridges with @LamarrInstitute 🥰
Pittsburgh you have been good to us! So much fruitful exchange with groups at @CarnegieMellon and @PittTweet, many opportunities for future research of our @LamarrInstitute. Today, onwards to St. Louis 🛬 – at Pittsburgh, PA
Raphael Fischer retweeted
👏 Today, we we will follow up on these initial meetings and take up many more at @CarnegieMellon and the University of Pittsburgh (@PittTweet) where the #Lamarr delegates will engage in in-depth scientific working sessions with various research groups on-site. (3/3)
What a start into the week, kicking off our @LamarrInstitute US delegation visit (in collaboration with @uniallianz NYC)! 😁 Great talks, lots of exchange, can't wait for the upcoming days in Pittsburgh and St. Louis. (HMU if you're in the area)!
Well-arrived in NYC for our @LamarrInstitute US delegation - let's science, but international! #aidelegation @MuckeSascha – at Manhattan, NY
Replying to @ECMLPKDD @DAMI_Social
link seems to be broken :/
Wondering how DL inference can be performed efficiently on the edge?💡Our new paper unveils practical insights of utilizing USB accelerators by @intel and @GoogleAI researchsquare.com/article/r…























