RISO, LUIGI
RISO, LUIGI
CULTURE, POLITICA E SOCIETA'
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Risultati 1 - 7 di 7 (tempo di esecuzione: 0.01 secondi).
Automatic variable selection for MIDAS regressions: an application
2022-01-01 Consuelo Rubina Nava, Luigi Riso, Maria Grazia Zoia
Concept Drift Estimation with Graphical Models
2022-01-01 Riso, Luigi; Guerzoni, Marco
Digital adoption and human capital upscaling: a regional study of the manufacturing sector
2024-01-01 Moncada R.; Carbonero F.; Geuna A.; Riso L.
Feature selection based on the best-path algorithm in high dimensional graphical models
2023-01-01 Luigi Riso; Maria G. Zoia ; Consuelo R. Nava
Forecasting innovative start-ups through automatic variable selection and MIDAS regressions
2023-01-01 Nava C.R.; Riso L.; Zoia M.G.
Time varying effects in survival analysis: a novel data-driven method for drift identification and variable selection
2024-01-01 Babutsidze Z.; Guerzoni M.; Riso L.
Use of Graphical Models in the field of Dimensionality Reduction Development of the new algorithms for automatic feature selection and the evaluation of the drift.
2021-03-22
Titolo | Data di pubblicazione | Autore(i) | File |
---|---|---|---|
Automatic variable selection for MIDAS regressions: an application | 2022 | Consuelo Rubina Nava, Luigi Riso, Maria Grazia Zoia | |
Concept Drift Estimation with Graphical Models | 2022 | Riso, Luigi; Guerzoni, Marco | |
Digital adoption and human capital upscaling: a regional study of the manufacturing sector | 2024 | Moncada R.; Carbonero F.; Geuna A.; Riso L. | |
Feature selection based on the best-path algorithm in high dimensional graphical models | 2023 | Luigi Riso; Maria G. Zoia ; Consuelo R. Nava | |
Forecasting innovative start-ups through automatic variable selection and MIDAS regressions | 2023 | Nava C.R.; Riso L.; Zoia M.G. | |
Time varying effects in survival analysis: a novel data-driven method for drift identification and variable selection | 2024 | Babutsidze Z.; Guerzoni M.; Riso L. | |
Use of Graphical Models in the field of Dimensionality Reduction Development of the new algorithms for automatic feature selection and the evaluation of the drift. | 2021 | - |