Leonardo Cella
TitleCited byYear
Exploring the semantic gap for movie recommendations
M Elahi, Y Deldjoo, F Bakhshandegan Moghaddam, L Cella, S Cereda, ...
Proceedings of the Eleventh ACM Conference on Recommender Systems, 326-330, 2017
212017
Content-based approaches for cold-start job recommendations
M Bianchi, F Cesaro, F Ciceri, M Dagrada, A Gasparin, D Grattarola, ...
Proceedings of the Recommender Systems Challenge 2017, 1-5, 2017
72017
Deriving item features relevance from past user interactions
L Cella, S Cereda, M Quadrana, P Cremonesi
Proceedings of the 25th Conference on User Modeling, Adaptation andá…, 2017
72017
Efficient linear bandits through matrix sketching
I Kuzborskij, L Cella, N Cesa-Bianchi
arXiv preprint arXiv:1809.11033, 2018
22018
Modelling User Behaviors with Evolving Users and Catalogs of Evolving Items
L Cella
Adjunct Publication of the 25th Conference on User Modeling, Adaptation andá…, 2017
22017
A supervised learning approach to swaption calibration
L CELLA
Italy, 2016
22016
Stochastic Bandits with Delay-Dependent Payoffs
L Cella, N Cesa-Bianchi
arXiv preprint arXiv:1910.02757, 2019
2019
Efficient Context-Aware Sequential Recommender System
L Cella
Companion Proceedings of the The Web Conference 2018, 1391-1394, 2018
2018
Estimate features relevance for groups of users
S Cereda, L Cella, P Cremonesi
IIR 2017 - 8th Italian Information Retrieval Workshop, 80-83, 2017
2017
Kernalized Collaborative Contextual Bandits.
L Cella, R Gaudel, P Cremonesi
RecSys Posters, 2017
2017
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Articles 1–10