Counterfactual Contextual Multi-Armed Bandit: a Real-World Application to Diagnose Apple Diseases

no code implementations • 8 Feb 2021 • Gabriele Sottocornola, Fabio Stella, Markus Zanker

Specifically, this paper addresses the problem of sequentially optimizing for the best diagnosis, leveraging past interactions with the system and their contextual information (i. e. the evidence provided by the users).

Active Learning counterfactual +1

Personalised novel and explainable matrix factorisation

no code implementations • 25 Jul 2019 • Ludovik Coba, Panagiotis Symeonidis, Markus Zanker

In this paper, to the best of our knowledge, we propose a new model, denoted as NEMF, that allows to trade-off the MF performance with respect to the criteria of novelty and explainability, while only minimally compromising on accuracy.

Decision Making Recommendation Systems