Post-conference: ECML-PKDD 2017

ECML-PKDD 2017 was very pleasant and nice. Skopje was an unexpected surprise. I am happy with each new conference that I attend, always meeting new people doing very good research. The community there was very nice in general!

I presented my paper at Matrix and Tensor Factorization session, and I was particularly happy with that, because even though the application we are working is recommender systems, we are focusing on the methods and proposing new factorization methods and models. Later in the night, we had the poster (poster-ecml2017) session at the Macedonian Opera & Ballet and afterward headed to the wine festival, just outside.

For thoseĀ interested, my presentation slides here:

Recommender Systems and Deep Learning: paper links

This semester I will be advising some master students on their final project. At this point, they don’t select a specific topic but should look into a given area to find specific research question and some of them will definitely work on Deep Learning and Recommender Systems. Especially because we (the NTNU-AILab group) had a very nice experience last year where one master student doing work on RNN for session-based recommendation managed to have a work accepted at DLRS 2017. So, I decided to make a small selection of the papers related to this topic, focusing on WSDM, WWW, KDD, CIKM, RecSys, ICLR, DLRS and some other specific conferences in the last three years (2015,2016 and 2017). The result is a list of 45 papers, with many distinct ideas, but also some common threads (Matrix Factorization to CNN or LSTM, Session-based methods using RNN, etc). We will not discuss the different ideas, but I will just post the link here because some people might be interested in that.

https://github.com/zehsilva/recsys-deeplearning-info