Open Ph.D. Positions in Automated Machine Learning (AutoML), Recommender Systems, Meta-Learning, Algorithm Selection, and Federated Learning — Trinity College Dublin, Irland (Sept. ’20)

This is a continuous call until 2022, with student intakes in September every year (and potentially in March). Next deadline is the 29th of February 2020 for a start in September 2020 for the CRT-AI, and 18th of March for the D-Real CRT. Science Foundation Ireland (SFI) agreed to fund Read more…

Multi-stream Data Analytics for Enhanced Performance Prediction in Fantasy Football [Pre-Print]

http://aics2019.datascienceinstitute.ie/papers/aics_27.pdf Abstract. Fantasy Premier League (FPL) performance predictors tend to base their algorithms purely on historical statistical data. The main problems with this approach is that external factors such as injuries, managerial decisions and other tournament match statistics can never be factored into the final predictions. In this paper, we Read more…

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…

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…

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…

The Architecture of Mr. DLib’s Scientific Recommender-System API

Our manuscript “The Architecture of Mr. DLib’s Scientific Recommender-System API” got accepted at the “26th Irish Conference on Artificial Intelligence and Cognitive Science” (AICS), and here is the pre-print version (HTML below; PDF on arxiv). The bibliographic BibTeX data is: @InProceedings{Beel2018MDLArch, author = {Beel, Joeran and Collins, Andrew and Aizawa, Read more…