LensKit 0.14.0 released (“Cleaning Up”)
LensKit just announced on Twitter that they released a new version of LensKit, one of the most popular recommender-systems software libraries. It seems there were no new algorithms being added, but a lot of cleanups were made that should improve the usability of LensKit. Either way, it’s great to see that LensKit is constantly being maintained and improved for many many years. The current release was based on the work of Michael Ekstrand and Adam Keener.
HetSeq: Training BERT on a random assortment of GPUs [Yifan Ding et al.]
Recommender-Systems Version Control: TensorFlow releases ‘Machine Learning Metadata (MLMD)’
TensorFlow introduces ‘TensorFlow Recommenders’ (TFRS)
About The Author
Joeran Beel
I am the founder of Recommender-Systems.com and head of the Intelligent Systems Group (ISG) at the University of Siegen, Germany https://isg.beel.org. We conduct research in recommender-systems (RecSys), personalization and information retrieval (IR) as well as on automated machine learning (AutoML), meta-learning and algorithm selection. Domains we are particularly interested in include smart places, eHealth, manufacturing (industry 4.0), mobility, visual computing, and digital libraries. We founded or maintain, among others, LensKit-Auto, Darwin & Goliath, Mr. DLib, and Docear, each with thousand of users; we contributed to TensorFlow, JabRef and others; and we developed the first prototypes of automated recommender systems (AutoSurprise and Auto-CaseRec) and Federated Meta Learning (FMLearn Server and Client).