Darwin & Goliath, Recommendations As a Service in our Blog

Darwin & Goliath: A White-Label Recommender-System As-a-Service with Automated Algorithm-Selection

This is the pre-print of our upcoming publication at the 13th ACM Conference on Recommender Systems (RecSys’19). Joeran Beel, Alan Griffin, and Conor O’Shea. 2019. Darwin & Goliath: A White-Label Recommender-System As-a-Service with Automated Algorithm-Selection. In Proceedings of the 13th ACM Conference on Recommender Systems (RecSys’19). ACM, New York, NY, Read more…

4 of our Submissions Got Accepted at the ACM Recommender Systems Conference (RecSys’19)

Four of our poster and demo submissions got accepted for presentation at the 13th ACM Recommender Systems Conference (RecSys 2019) in Copenhagen in September. The accepted submissions are as follows (pre-prints will follow soon): Darwin & Goliath: A White-Label Recommender-System As-a-Service with Automated Algorithm-Selection Joeran Beel, Alan Griffin, Conor O’Shea Read more…

I Join the Scientific Advisory Board of the German Academic Exchange Service (DAAD) for IFI Scholarships in Artificial Intelligence and Machine Learning

Update 2019-08-14 DAAD published a new website for the IFI programme: www.daad.de/ifi I was invited to join the scientific advisory board for the new IFI programme of the German Academic Exchange Service (Deutscher Akademischer Austauschdienst – DAAD). The IFI programme (German: “Internationale Forschungsaufenthalte für Informatiker_Innen”) is the successor of the Read more…

New Publication: Choice Overload and Recommendation Effectiveness in Related-Article Recommendations

The International Journal on Digital Libraries (IJDL) published our manuscript “Choice Overload and Recommendation Effectiveness in Related-Article Recommendations: Analyzing the Sowiport Digital Library”. The paper is freely available as open access via Springer. The paper is an extended version of a previous paper published at the 5th International Workshop on Read more…

Federated Meta-Learning: Democratizing Algorithm Selection Across Disciplines and Software Libraries (Proposal)

Update: Read the full manuscript, which was presented at the AutoML workshop, here. Introduction There is an ever-growing number of tools for automating the machine learning pipeline, both commercial and open source. Auto-sklearn [11, 15], Auto Weka [14], ML-Plan [18], and H2O.ai are only some examples. In addition, the auto* Read more…

Upcoming Breakfast Seminar for Potential Postdoctoral ELITE-S Applicants (Standardization in ML, AI, and RecSys)

The ELITE-S initiative organizes a breakfast seminar to bring together potential applicants and supervisors. Every postdoctoral researcher, who is interested in standardization in the field of recommender systems, machine learning, and artificial intelligence, is sincerely invited to join the breakfast. During the seminar, you will learn more about the 2-year Read more…

ELITE-S: 16 Postdoctoral Fellowships in ICT Standardisation — Recommender-Systems, (Automated) Machine Learning, APIs, …

Update: Deadline extended to July 15th, 2019. ELITE-S provides up to 16 postdoctoral fellowships to work for 2 years in the ADAPT Research Centre at Trinity College Dublin, University College Dublin, or other Irish universities as well as with an industry partner. ELITE-S is a EU Marie Skłodowska-Curie COFUND Action. Read more…