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Matteo Ruffini
Matteo Ruffini
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Title
Cited by
Cited by
Year
Generating synthetic but plausible healthcare record datasets
L Avi˝ˇ, M Ruffini, R GavaldÓ
arXiv preprint arXiv:1807.01514, 2018
242018
Clustering Patients with Tensor Decomposition
M Ruffini, R GavaldÓ, E Limˇn
Machine Learning for Healthcare (MLHC), 2017, 2017
182017
Uncalibrated view synthesis with homography interpolation
P Fragneto, A Fusiello, B Rossi, L Magri, M Ruffini
2012 Second International Conference on 3D Imaging, Modeling, Processingá…, 2012
72012
Hierarchical methods of moments
M Ruffini, G Rabusseau, B Balle
Advances in Neural Information Processing Systems 30, 2017
42017
A new method of moments for latent variable models
M Ruffini, M Casanellas, R GavaldÓ
Machine Learning 107 (8), 1431-1455, 2018
32018
Is the Brownian bridge a good noise model on the boundary of a circle?
G Aletti, M Ruffini
Annals of the Institute of Statistical Mathematics 69 (2), 389-416, 2017
32017
Is the Brownian bridge a good noise model on the circle?
G Aletti, M Ruffini
arXiv preprint arXiv:1210.8245, 2012
32012
Ranker-agnostic contextual position bias estimation
OB Mayor, V Bellini, A Buchholz, G Di Benedetto, DM Granziol, M Ruffini, ...
arXiv preprint arXiv:2107.13327, 2021
22021
A new spectral method for latent variable models
M Ruffini, M Casanellas Rius, R GavaldÓ Mestre
Machine learning 107 (8-10), 1431-1455, 2018
22018
Modeling Position Bias Ranking for Streaming Media Services
M Ruffini, V Bellini, A Buchholz, G Di Benedetto, Y Stein
12022
Low-variance estimation in the Plackett-Luce model via quasi-Monte Carlo sampling
A Buchholz, JM Lichtenberg, G Di Benedetto, Y Stein, V Bellini, M Ruffini
arXiv preprint arXiv:2205.06024, 2022
2022
Fair Effect Attribution in Parallel Online Experiments
A Buchholz, V Bellini, G Di Benedetto, Y Stein, M Ruffini, F Moerchen
2022
Ranker-agnostic Contextual Position Bias Estimation
O Barbany Mayor, V Bellini, A Buchholz, G Di Benedetto, DM Granziol, ...
arXiv e-prints, arXiv: 2107.13327, 2021
2021
Learning latent variable models: efficient algorithms and applications
M Ruffini
Universitat PolitŔcnica de Catalunya, 2019
2019
A canonical form for Gaussian periodic processes
G Aletti, M Ruffini
arXiv preprint arXiv:1202.6182, 2012
2012
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