CORIZZO, ROBERTO
CORIZZO, ROBERTO
Aerial scene classification through fine-tuning with adaptive learning rates and label smoothing
2020-01-01 Petrovska, B.; Atanasova-Pacemska, T.; Corizzo, R.; Mignone, P.; Lameski, P.; Zdravevski, E.
Air pollution prediction with multi-modal data and deep neural networks
2020-01-01 Kalajdjieski, J.; Zdravevski, E.; Corizzo, R.; Lameski, P.; Kalajdziski, S.; Pires, I. M.; Garcia, N. M.; Trajkovik, V.
An OWL Ontology for Supporting Semantic Services in Big Data Platforms
2018-01-01 Redavid, D.; Corizzo, R.; Malerba, D.
Anomaly Detection and Repair for Accurate Predictions in Geo-distributed Big Data
2019-01-01 Corizzo, R.; Ceci, M.; Japkowicz, N.
Big Data Analytics and Predictive Modeling Approaches for the Energy Sector
2019-01-01 Corizzo, R.; Ceci, M.; Malerba, D.
Big data techniques for renewable energy market
2014-01-01 Ceci, Michelangelo; Cassavia, N; Corizzo, R; Dicosta, P; Malerba, D; Maria, G; Masciari, E; Pastura, C.
Big Data Techniques For Renewable Energy Market (Discussion Paper)
2014-01-01 Ceci, M; Cassavia, N; Corizzo, R; Dicosta, P; Malerba, Donato; Maria, G; Masciari, E; Pastura, C.
Big data techniques for supporting accurate predictions of energy production from renewable sources
2015-01-01 Ceci, Michelangelo; Corizzo, Roberto; Fumarola, Fabio; Ianni, Michele; Malerba, Donato; Maria, Gaspare; Masciari, Elio; Oliverio, Marco; Rashkovska, Aleksandra
Deep learning for feature extraction in remote sensing: A case-study of aerial scene classification
2020-01-01 Petrovska, B.; Zdravevski, E.; Lameski, P.; Corizzo, R.; Stajduhar, I.; Lerga, J.
Deep learning versus conventional learning in data streams with concept drifts
2019-01-01 Ryan, S.; Corizzo, R.; Kiringa, I.; Japkowicz, N.
DENCAST: distributed density-based clustering for multi-target regression
2019-01-01 Corizzo, R.; Pio, G.; Ceci, M.; Malerba, D.
ECHAD: Embedding-Based Change Detection from Multivariate Time Series in Smart Grids
2020-01-01 Ceci, M.; Corizzo, R.; Japkowicz, N.; Mignone, P.; Pio, G.
Explainable Spatio-Temporal Graph Modeling
2023-01-01 Altieri, M.; Ceci, M.; Corizzo, R.
Feature extraction based on word embedding models for intrusion detection in network traffic
2020-01-01 Corizzo, Roberto; Zdravevski, Eftim; Russell, Myles; Vagliano, Andrew; Japkowicz, Nathalie
Forecasting via distributed density-based clustering
2017-01-01 Corizzo, Roberto; Pio, Gianvito; Ceci, Michelangelo; Malerba, Donato
Innovative power operating center management exploiting big data techniques.
2014-01-01 Ceci, Michelangelo; Cassavia, N; Corizzo, R; Dicosta, P; Malerba, D; Maria, G; Masciari, E; Pastura, C.
Literature on applied machine learning in metagenomic classification: A scoping review
2020-01-01 Tonkovic, P.; Kalajdziski, S.; Zdravevski, E.; Lameski, P.; Corizzo, R.; Pires, I. M.; Garcia, N. M.; Loncar-Turukalo, T.; Trajkovik, V.
Multi-aspect renewable energy forecasting
2021-01-01 Corizzo, R.; Ceci, M.; Fanaee-T, H.; Gama, J.
Multi-horizon air pollution forecasting with deep neural networks
2021-01-01 Arsov, M.; Zdravevski, E.; Lameski, P.; Corizzo, R.; Koteli, N.; Gramatikov, S.; Mitreski, K.; Trajkovik, V.
One-Class Ensembles for Rare Genomic Sequences Identification
2020-01-01 Kaufmann, J.; Asalone, K.; Corizzo, R.; Saldanha, C.; Bracht, J.; Japkowicz, N.
Titolo | Data di pubblicazione | Autore(i) | File |
---|---|---|---|
Aerial scene classification through fine-tuning with adaptive learning rates and label smoothing | 1-gen-2020 | Petrovska, B.; Atanasova-Pacemska, T.; Corizzo, R.; Mignone, P.; Lameski, P.; Zdravevski, E. | |
Air pollution prediction with multi-modal data and deep neural networks | 1-gen-2020 | Kalajdjieski, J.; Zdravevski, E.; Corizzo, R.; Lameski, P.; Kalajdziski, S.; Pires, I. M.; Garcia, N. M.; Trajkovik, V. | |
An OWL Ontology for Supporting Semantic Services in Big Data Platforms | 1-gen-2018 | Redavid, D.; Corizzo, R.; Malerba, D. | |
Anomaly Detection and Repair for Accurate Predictions in Geo-distributed Big Data | 1-gen-2019 | Corizzo, R.; Ceci, M.; Japkowicz, N. | |
Big Data Analytics and Predictive Modeling Approaches for the Energy Sector | 1-gen-2019 | Corizzo, R.; Ceci, M.; Malerba, D. | |
Big data techniques for renewable energy market | 1-gen-2014 | Ceci, Michelangelo; Cassavia, N; Corizzo, R; Dicosta, P; Malerba, D; Maria, G; Masciari, E; Pastura, C. | |
Big Data Techniques For Renewable Energy Market (Discussion Paper) | 1-gen-2014 | Ceci, M; Cassavia, N; Corizzo, R; Dicosta, P; Malerba, Donato; Maria, G; Masciari, E; Pastura, C. | |
Big data techniques for supporting accurate predictions of energy production from renewable sources | 1-gen-2015 | Ceci, Michelangelo; Corizzo, Roberto; Fumarola, Fabio; Ianni, Michele; Malerba, Donato; Maria, Gaspare; Masciari, Elio; Oliverio, Marco; Rashkovska, Aleksandra | |
Deep learning for feature extraction in remote sensing: A case-study of aerial scene classification | 1-gen-2020 | Petrovska, B.; Zdravevski, E.; Lameski, P.; Corizzo, R.; Stajduhar, I.; Lerga, J. | |
Deep learning versus conventional learning in data streams with concept drifts | 1-gen-2019 | Ryan, S.; Corizzo, R.; Kiringa, I.; Japkowicz, N. | |
DENCAST: distributed density-based clustering for multi-target regression | 1-gen-2019 | Corizzo, R.; Pio, G.; Ceci, M.; Malerba, D. | |
ECHAD: Embedding-Based Change Detection from Multivariate Time Series in Smart Grids | 1-gen-2020 | Ceci, M.; Corizzo, R.; Japkowicz, N.; Mignone, P.; Pio, G. | |
Explainable Spatio-Temporal Graph Modeling | 1-gen-2023 | Altieri, M.; Ceci, M.; Corizzo, R. | |
Feature extraction based on word embedding models for intrusion detection in network traffic | 1-gen-2020 | Corizzo, Roberto; Zdravevski, Eftim; Russell, Myles; Vagliano, Andrew; Japkowicz, Nathalie | |
Forecasting via distributed density-based clustering | 1-gen-2017 | Corizzo, Roberto; Pio, Gianvito; Ceci, Michelangelo; Malerba, Donato | |
Innovative power operating center management exploiting big data techniques. | 1-gen-2014 | Ceci, Michelangelo; Cassavia, N; Corizzo, R; Dicosta, P; Malerba, D; Maria, G; Masciari, E; Pastura, C. | |
Literature on applied machine learning in metagenomic classification: A scoping review | 1-gen-2020 | Tonkovic, P.; Kalajdziski, S.; Zdravevski, E.; Lameski, P.; Corizzo, R.; Pires, I. M.; Garcia, N. M.; Loncar-Turukalo, T.; Trajkovik, V. | |
Multi-aspect renewable energy forecasting | 1-gen-2021 | Corizzo, R.; Ceci, M.; Fanaee-T, H.; Gama, J. | |
Multi-horizon air pollution forecasting with deep neural networks | 1-gen-2021 | Arsov, M.; Zdravevski, E.; Lameski, P.; Corizzo, R.; Koteli, N.; Gramatikov, S.; Mitreski, K.; Trajkovik, V. | |
One-Class Ensembles for Rare Genomic Sequences Identification | 1-gen-2020 | Kaufmann, J.; Asalone, K.; Corizzo, R.; Saldanha, C.; Bracht, J.; Japkowicz, N. |