298 citations · 626 across the 17 of their papers we have counts for
3 papers · 1 filter
Bandits Warm-up Cold Recommender Systems
Jérémie Mary, Romaric Gaudel, Preux Philippe
We address the cold start problem in recommendation systems assuming no contextual information is available neither about users, nor items. We consider the case in which we only ha…
Cold-start Problems in Recommendation Systems via Contextual-bandit Algorithms
Hai Thanh Nguyen, Jérémie Mary, Philippe Preux
In this paper, we study a cold-start problem in recommendation systems where we have completely new users entered the systems. There is not any interaction or feedback of the new u…
Improving offline evaluation of contextual bandit algorithms via bootstrapping techniques
Olivier Nicol, Jérémie Mary, Philippe Preux
In many recommendation applications such as news recommendation, the items that can be rec- ommended come and go at a very fast pace. This is a challenge for recommender systems (R…