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2020 – today
- 2022
[b1]Stefano Piersanti:
Will it fail and why? A large case study of company default prediction with highly interpretable machine learning models. Sapienza University of Rome, Italy, 2022- [c4]Stefano Piersanti:
Improve Default Prediction in Highly Unbalanced Context. PKDD/ECML Workshops (2) 2022: 62-78 - 2020
- [i1]Tesi Aliaj, Aris Anagnostopoulos, Stefano Piersanti:
Firms Default Prediction with Machine Learning. CoRR abs/2002.11705 (2020)
2010 – 2019
- 2019
- [c3]Tesi Aliaj, Aris Anagnostopoulos
, Stefano Piersanti:
Firms Default Prediction with Machine Learning. MIDAS@PKDD 2019: 47-59 - 2017
- [j1]Francesco de Paulis, Stefano Piersanti, Qian Wang, Jonghyun Cho, Nicholas Erickson, Brice Achkir, Jun Fan, James L. Drewniak, Antonio Orlandi:
TEM-Like Launch Geometries and Simplified De-embedding for Accurate Through Silicon Via Characterization. IEEE Trans. Instrum. Meas. 66(4): 792-801 (2017) - 2013
- [c2]Dajana Cassioli, Luca Alfredo Annoni, Stefano Piersanti:
Characterization of path loss and delay spread of 60-GHz UWB channels vs. frequency. ICC 2013: 5153-5157 - 2012
- [c1]Stefano Piersanti, Luca Alfredo Annoni, Dajana Cassioli:
Millimeter waves channel measurements and path loss models. ICC 2012: 4552-4556
Coauthor Index
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