Entries by Andreas Holzinger

Miniconf Thursday, 20th December 2018: Raphaël Marée

Raphaël MARÉE  from the Montefiori Institute, Unviersity of Liege will visit us in week 51 and give a lecture on Open and Collaborative Digital Pathology using Cytomine When: Thursday, 20th December, 2018, at 10:00 Where: BBMRI Conference Room (joint invitation of BBMRI, ADOPT and HCI-KDD) Address: Neue Stiftingtalstrasse 2/B/6, A-8010 Graz, Austria Download pdf, 72kB […]

Interactive Machine Learning: Experimental Evidence for the human-in-the-loop

Recent advances in automatic machine learning (aML) allow solving problems without any human intervention, which is excellent in certain domains, e.g. in autonomous cars, where we want to exclude the human from the loop and want fully automatic learning. However, sometimes a human-in-the-loop can be beneficial – particularly in solving computationally hard problems. We provide […]

AI, explain yourself !

“It’s time for AI to move out its adolescent, game-playing phase and take seriously the notions of quality and reliability.” There is an interesting commentary with interviews by Don MONROE in the recent Communications of the ACM, November 2018, Volume 61, Number 11, Pages 11-13, doi: 10.1145/3276742 which emphasizes the importance of explainability and the […]

What if the AI answers are wrong?

Cartoon no. 1838 from the xkcd [1] Web comic by Randall MUNROE [2] describes in a brilliant sarcastic way the state of the art in AI/machine learning today and shows us the current main problem directly. Of course you will always get results from one of your machine learning models. Just fill in your data […]

Project Feature Cloud – Pre-Project Meeting and Workshop successful

From October, 21-22, 2018, the project partners of the EU RIA 826078 FeatureCloud project (EUR 4,646,000,00) met at the Technische Universität München, Campus Weihenstephan.  Starting from January, 1, 2019 the project partners will work jointly for 60 months on awesome topics around federated machine learning and explainability. The project’s ground-breaking novel cloud-AI infrastructure will only […]

How different are Cats vs. Cells in Histopathology?

An awesome question stated in an article by Michael BEREKET and Thao NGUYEN (Febuary 7, 2018) brings it straight to the point: Deep learning has revolutionized the field of computer vision. So why are pathologists still spending their time looking at cells through microscopes? The most famous machine learning experiments have been done with recognizing […]

Yoshua Bengio emphasizes: Deep Learning needs Deep Understanding !

Yoshua BENGIO from the Canadian Institute for Advanced Research (CIFAR) emphasized during his workshop talk entitled “towards disentangling underlying explanatory factors”  (cool title) at the ICML 2018 in Stockholm, that the key for success in AI/machine learning is to understand the explanatory/causal factors and mechanisms. This means generalizing beyond identical independent data (i.i.d.); current machine […]

Explainable AI Session Keynote: Randy GOEBEL

We just had our keynote by Randy GOEBEL from the Alberta Machine Intelligence Institute (Amii), working on enhnancing understanding and innovation in artificial intelligence: https://cd-make.net/keynote-speaker-randy-goebel You can see his slides with friendly permission of Randy here (pdf, 2,680 kB): https://hci-kdd.org/wordpress/wp-content/uploads/2018/08/Goebel.XAI_.CD-MAKE.Aug30.2018.pdf Here you can read a preprint of our joint paper of our explainable ai session (pdf, […]

CD-MAKE Keynote by Klaus-Robert MÜLLER

Prof. Dr. Klaus-Robert MÜLLER from the TU Berlin was our keynote speaker on Tuesday, August, 28th, 2018 during our CD-MAKE conference at the University of Hamburg, see: https://cd-make.net/keynote-speaker-08-28-2018/ Klaus-Robert emphasized in his talk the “right of explanation” by the new European Union General Data Protection Regulations, but also shows some diffulties, challenges and future research […]

“Machine Learning and Knowledge Extraction” 2nd CD-MAKE Volume just appeared

The second Volume of the Springer LNCS Proceedings of the IFIP TC 5, TC 8/WG 8.4, 8.9, TC 12/WG 12.9 International Cross-Domain Conference, CD-MAKE Machine Learning & Knowledge Extraction just appeared, see: https://link.springer.com/book/10.1007/978-3-319-99740-7 >> Here the preprints of our papers: [1] Andreas Holzinger, Peter Kieseberg, Edgar Weippl & A Min Tjoa 2018. Current Advances, Trends […]