Sfoglia per Corso
Direct search methods for influence maximization problems
2022/2023 BERGAMASCHI, MATTEO
Directors' dealings: an analysis of their predictive power
2022/2023 ZANDEGIACOMO ORSOLINA, MATTEO
Dynamical low-rank training of neural networks
2021/2022 ZANGRANDO, EMANUELE
Eco-Friendly Wind Energy: Improving Radar Tracking Systems for Bird Monitoring
2022/2023 SECA REPAS GONCALVES, DIOGO
Enhanced Forecasting Models: Implementation and Comparative Analysis of Sibylla 5.0 with Prophet and NeuralProphet Algorithms
2023/2024 KOLOBOV, MIKHAIL
Enhancing Anomaly Detection: Integrating Human Feedback Through Active Learning
2023/2024 BAZ RADWAN, FAIROUZ
Enhancing Default Prediction with Mixed High-Frequency Market Data
2023/2024 TROGU, SOFIA POPE
Enhancing protein function prediction through statistical association and taxonomic enrichment analysis
2023/2024 PERTILE, ANDREA VALENTINA
Evaluation of deep learning transformers models for brain stroke lesions automatic segmentation
2021/2022 ARANGUREN, ANDRES
Evaluation of RNA velocity as a signal for the reconstruction of gene regulatory networks.
2021/2022 FARNEA, GRETA
Exact and heuristic algorithms for multi-robot system routing, oriented to underwater monitoring.
2021/2022 MIOLATO, MATTIA
Explainability in recommender systems: a comparative analysis of two transformer-based models
2023/2024 ORELLANA I RÍOS, JOAN
Explainability of machine learning models: A systematic review and a case study on BERT
2020/2021 ARCUDI, ALESSIO
Explaining Rocket time series classifier model
2022/2023 RASTEGAR, ARVIN
Exploiting Large Language Models to Train Automatic Detectors of Sensitive Data
2022/2023 DE RENZIS, SIMONE
EXPLORING CONVOLUTION FOR THE DETECTION OF MENTAL ATTENTION STATES
2021/2022 ANDOVSKA, SANDRA
Exploring Deep Learning Domain Adaptation performance: from Covariate shift to Wasserstein and beyond
2023/2024 FURLAN, MARCO
Exponential smoothing with neural networks: a TBATS-NN hybrid model for hierarchical time series forecasting
2023/2024 BIANCUCCI, FRANCESCO
Fairness in Rankings via Randomized Algorithms
2023/2024 KLIACHKIN, ANDRII
Federated Learning for an Autoencoder Based Recommendation System
2020/2021 EL KHALOUFI, YASMINE
| Tipologia | Anno | Titolo | Titolo inglese | Autore | File |
|---|---|---|---|---|---|
| Lauree magistrali | 2022 | Direct search methods for influence maximization problems | Direct search methods for influence maximization problems | BERGAMASCHI, MATTEO | |
| Lauree magistrali | 2022 | Directors' dealings: an analysis of their predictive power | Directors' dealings: an analysis of their predictive power | ZANDEGIACOMO ORSOLINA, MATTEO | |
| Lauree magistrali | 2021 | Dynamical low-rank training of neural networks | Dynamical low-rank training of neural networks | ZANGRANDO, EMANUELE | |
| Lauree magistrali | 2022 | Eco-Friendly Wind Energy: Improving Radar Tracking Systems for Bird Monitoring | Eco-Friendly Wind Energy: Improving Radar Tracking Systems for Bird Monitoring | SECA REPAS GONCALVES, DIOGO | |
| Lauree magistrali | 2023 | Enhanced Forecasting Models: Implementation and Comparative Analysis of Sibylla 5.0 with Prophet and NeuralProphet Algorithms | Enhanced Forecasting Models: Implementation and Comparative Analysis of Sibylla 5.0 with Prophet and NeuralProphet Algorithms | KOLOBOV, MIKHAIL | |
| Lauree magistrali | 2023 | Enhancing Anomaly Detection: Integrating Human Feedback Through Active Learning | Enhancing Anomaly Detection: Integrating Human Feedback Through Active Learning | BAZ RADWAN, FAIROUZ | |
| Lauree magistrali | 2023 | Enhancing Default Prediction with Mixed High-Frequency Market Data | Enhancing Default Prediction with Mixed High-Frequency Market Data | TROGU, SOFIA POPE | |
| Lauree magistrali | 2023 | Enhancing protein function prediction through statistical association and taxonomic enrichment analysis | Enhancing protein function prediction through statistical association and taxonomic enrichment analysis | PERTILE, ANDREA VALENTINA | |
| Lauree magistrali | 2021 | Evaluation of deep learning transformers models for brain stroke lesions automatic segmentation | Evaluation of deep learning transformers models for brain stroke lesions automatic segmentation | ARANGUREN, ANDRES | |
| Lauree magistrali | 2021 | Evaluation of RNA velocity as a signal for the reconstruction of gene regulatory networks. | Evaluation of RNA velocity as a signal for the reconstruction of gene regulatory networks. | FARNEA, GRETA | |
| Lauree magistrali | 2021 | Exact and heuristic algorithms for multi-robot system routing, oriented to underwater monitoring. | Exact and heuristic algorithms for multi-robot system routing, oriented to underwater monitoring. | MIOLATO, MATTIA | |
| Lauree magistrali | 2023 | Explainability in recommender systems: a comparative analysis of two transformer-based models | Explainability in recommender systems: a comparative analysis of two transformer-based models | ORELLANA I RÍOS, JOAN | |
| Lauree magistrali | 2020 | Explainability of machine learning models: A systematic review and a case study on BERT | Explainability of machine learning models: A systematic review and a case study on BERT | ARCUDI, ALESSIO | |
| Lauree magistrali | 2022 | Explaining Rocket time series classifier model | Explaining Rocket time series classifier model | RASTEGAR, ARVIN | |
| Lauree magistrali | 2022 | Exploiting Large Language Models to Train Automatic Detectors of Sensitive Data | Exploiting Large Language Models to Train Automatic Detectors of Sensitive Data | DE RENZIS, SIMONE | |
| Lauree magistrali | 2021 | EXPLORING CONVOLUTION FOR THE DETECTION OF MENTAL ATTENTION STATES | EXPLORING CONVOLUTION FOR THE DETECTION OF MENTAL ATTENTION STATES | ANDOVSKA, SANDRA | |
| Lauree magistrali | 2023 | Exploring Deep Learning Domain Adaptation performance: from Covariate shift to Wasserstein and beyond | Exploring Deep Learning Domain Adaptation performance: from Covariate shift to Wasserstein and beyond | FURLAN, MARCO | |
| Lauree magistrali | 2023 | Exponential smoothing with neural networks: a TBATS-NN hybrid model for hierarchical time series forecasting | Exponential smoothing with neural networks: a TBATS-NN hybrid model for hierarchical time series forecasting | BIANCUCCI, FRANCESCO | |
| Lauree magistrali | 2023 | Fairness in Rankings via Randomized Algorithms | Fairness in Rankings via Randomized Algorithms | KLIACHKIN, ANDRII | |
| Lauree magistrali | 2020 | Federated Learning for an Autoencoder Based Recommendation System | Federated Learning for an Autoencoder Based Recommendation System | EL KHALOUFI, YASMINE |
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