Fabio Stella

Publication Activity (10 Years)

Years Active: 1997-2024
Publications (10 Years): 50

Top Topics

Causal Discovery

Inventory Control

Reinforcement Learning

Bayesian Networks

Top Venues

Int. J. Approx. Reason.

Publications

Fabio Stella, Francesco Calimeri, Mauro Dragoni
Special issue on learning from multiple data sources for decision making in health care. J. Biomed. Informatics 153 (2024)
Francesco Stranieri, Fabio Stella, Chaaben Kouki
Performance of deep reinforcement learning algorithms in two-echelon inventory control systems. Int. J. Prod. Res. 62 (17) (2024)
Emanuele Cavenaghi, Alessio Zanga, Alessandro Rimoldi, Paolo Minasi, Markus Zanker, Fabio Stella
Analysis of Relevant Factors in Online Hotel Recommendation Through Causal Models. RecTour@RecSys (2023)
Alessio Zanga, Alice Bernasconi, Peter J. F. Lucas, Hanny Pijnenborg, Casper Reijnen, Marco Scutari, Fabio Stella
Causal Discovery with Missing Data in a Multicentric Clinical Study. AIME (2023)
Emanuele Cavenaghi, Gabriele Sottocornola, Fabio Stella, Markus Zanker
A Systematic Study on Reproducibility of Reinforcement Learning in Recommendation Systems. Trans. Recomm. Syst. 1 (3) (2023)
Alice Bernasconi, Alessio Zanga, Peter J. F. Lucas, Marco Scutari, Fabio Stella
Towards a Transportable Causal Network Model Based on Observational Healthcare Data. CoRR (2023)
Francesco Craighero, Fabrizio Angaroni, Fabio Stella, Chiara Damiani, Marco Antoniotti, Alex Graudenzi
Unity is strength: Improving the detection of adversarial examples with ensemble approaches. Neurocomputing 554 (2023)
Francesco Stranieri, Alberto Archetti, Enrico Robbiano, Chaaben Kouki, Fabio Stella
Drug Inventory Control: Human Decisions Versus Deep Reinforcement Learning (short paper). AIABI@AI*IA (2023)
Carlos Villa-Blanco, Alessandro Bregoli, Concha Bielza, Pedro Larrañaga, Fabio Stella
Constraint-based and hybrid structure learning of multidimensional continuous-time Bayesian network classifiers. Int. J. Approx. Reason. 159 (2023)
Alessandro Bregoli, Karin Rathsman, Marco Scutari, Fabio Stella, Søren Wengel Mogensen
Analyzing Complex Systems with Cascades Using Continuous-Time Bayesian Networks. CoRR (2023)
Alessandro Bregoli, Karin Rathsman, Marco Scutari, Fabio Stella, Søren Wengel Mogensen
Analyzing Complex Systems with Cascades Using Continuous-Time Bayesian Networks. TIME (2023)
Alessio Zanga, Alice Bernasconi, Peter J. F. Lucas, Hanny Pijnenborg, Casper Reijnen, Marco Scutari, Fabio Stella
Causal Discovery with Missing Data in a Multicentric Clinical Study. CoRR (2023)
Alessio Zanga, Alice Bernasconi, Peter J. F. Lucas, Hanny Pijnenborg, Casper Reijnen, Marco Scutari, Fabio Stella
Risk Assessment of Lymph Node Metastases in Endometrial Cancer Patients: A Causal Approach. CoRR (2023)
Alessio Zanga, Fabio Stella
A Survey on Causal Discovery: Theory and Practice. CoRR (2023)
Emanuele Cavenaghi, Lorenzo Camaione, Paolo Minasi, Gabriele Sottocornola, Fabio Stella, Markus Zanker
An Online Experiment of a Price-Based Re-Rank Algorithm. RecTour@RecSys (2022)
Alessio Zanga, Alice Bernasconi, Peter J. F. Lucas, Hanny Pijnenborg, Casper Reijnen, Marco Scutari, Fabio Stella
Risk Assessment of Lymph Node Metastasis in Endometrial Cancer Patients: A Causal Approach. HC@AIxIA (2022)
Gabriele Sottocornola, Sanja Baric, Maximilian Nocker, Fabio Stella, Markus Zanker
Picture-based and conversational decision support to diagnose post-harvest apple diseases. Expert Syst. Appl. 189 (2022)
Francesco Stranieri, Fabio Stella
Deep Reinforcement Learning for a Two-Echelon Supply Chain with Seasonal Demand. CoRR (2022)
Marco Gigli, Fabio Stella
Parametric Bandits for Search Engine Marketing Optimisation. PAKDD (3) (2022)
Alessio Zanga, Elif Ozkirimli, Fabio Stella
A Survey on Causal Discovery: Theory and Practice. Int. J. Approx. Reason. 151 (2022)
Carlos Villa-Blanco, Alessandro Bregoli, Concha Bielza, Pedro Larrañaga, Fabio Stella
Structure learning algorithms for multidimensional continuous-time Bayesian network classifiers. PGM (2022)
Emanuele Cavenaghi, Lorenzo Camaione, Paolo Minasi, Gabriele Sottocornola, Fabio Stella, Markus Zanker
An Analysis of User Click Behaviour in Online Hotel Search. IIR (2022)
Gabriele Sottocornola, Fabio Stella, Markus Zanker
Counterfactual Contextual Multi-Armed Bandit to Diagnose Post-Harvest Diseases of Apple. WI/IAT (2021)
Gabriele Sottocornola, Fabio Stella, Markus Zanker
Counterfactual Contextual Multi-Armed Bandit: a Real-World Application to Diagnose Apple Diseases. CoRR (2021)
Emanuele Cavenaghi, Gabriele Sottocornola, Fabio Stella, Markus Zanker
Non Stationary Multi-Armed Bandit: Empirical Evaluation of a New Concept Drift-Aware Algorithm. Entropy 23 (3) (2021)
Francesco Craighero, Fabrizio Angaroni, Fabio Stella, Chiara Damiani, Marco Antoniotti, Alex Graudenzi
EAD: an ensemble approach to detect adversarial examples from the hidden features of deep neural networks. CoRR (2021)
Gabriele Sottocornola, Sanja Baric, Fabio Stella, Markus Zanker
Case Study on the Development of a Recommender for Apple Disease Diagnosis with a Knowledge-based Bayesian Network (Long paper). KaRS/ComplexRec@RecSys (2021)
Alessandro Bregoli, Marco Scutari, Fabio Stella
A constraint-based algorithm for the structural learning of continuous-time Bayesian networks. Int. J. Approx. Reason. 138 (2021)
Andrea Ruggieri, Francesco Stranieri, Fabio Stella, Marco Scutari
Hard and Soft EM in Bayesian Network Learning from Incomplete Data. CoRR (2020)
Francesco Craighero, Fabrizio Angaroni, Alex Graudenzi, Fabio Stella, Marco Antoniotti
Investigating the Compositional Structure Of Deep Neural Networks. CoRR (2020)
Andrea Ruggieri, Francesco Stranieri, Fabio Stella, Marco Scutari
Hard and Soft EM in Bayesian Network Learning from Incomplete Data. Algorithms 13 (12) (2020)
Alessandro Bregoli, Marco Scutari, Fabio Stella
Constraint-Based Learning for Continuous-Time Bayesian Networks. CoRR (2020)
Francesco Craighero, Alex Graudenzi, Fabrizio Angaroni, Fabio Stella, Marco Antoniotti
Understanding Deep Learning with Activation Pattern Diagrams. XAI.it@AI*IA (2020)
Alessandro Bregoli, Marco Scutari, Fabio Stella
Constraing-Based Learning for Continous-Time Bayesian Networks. PGM (2020)
Francesco Craighero, Fabrizio Angaroni, Alex Graudenzi, Fabio Stella, Marco Antoniotti
Investigating the Compositional Structure of Deep Neural Networks. LOD (1) (2020)
Gabriele Sottocornola, Maximilian Nocker, Fabio Stella, Markus Zanker
Contextual multi-armed bandit strategies for diagnosing post-harvest diseases of apple. IUI (2020)
Italo Zoppis, Alessio Zanga, Sara Manzoni, Giulia Cisotto, Angela Morreale, Fabio Stella, Giancarlo Mauri
An Attention-based Architecture for EEG Classification. BIOSIGNALS (2020)
Mauro Scanagatta, Antonio Salmerón, Fabio Stella
A survey on Bayesian network structure learning from data. Prog. Artif. Intell. 8 (4) (2019)
Manxia Liu, Fabio Stella, Arjen Hommersom, Peter J. F. Lucas, Lonneke Boer, Erik Bischoff
A comparison between discrete and continuous time Bayesian networks in learning from clinical time series data with irregularity. Artif. Intell. Medicine 95 (2019)
Manxia Liu, Fabio Stella, Arjen Hommersom, Peter J. F. Lucas
Representing Hypoexponential Distributions in Continuous Time Bayesian Networks. IPMU (3) (2018)
Maximilian Nocker, Gabriele Sottocornola, Markus Zanker, Sanja Baric, Greice Amaral Carneiro, Fabio Stella
Picture-based navigation for diagnosing post-harvest diseases of apple. RecSys (2018)
Simone Villa, Fabio Stella
Learning Continuous Time Bayesian Networks in Non-stationary Domains. IJCAI (2018)
Manxia Liu, Fabio Stella, Arjen Hommersom, Peter J. F. Lucas
Making Continuous Time Bayesian Networks More Flexible. PGM (2018)
Maha Amami, Rim Faiz, Fabio Stella, Gabriella Pasi
A graph based approach to scientific paper recommendation. WI (2017)
Gabriele Sottocornola, Fabio Stella, Markus Zanker, Francesco Canonaco
Towards a deep learning model for hybrid recommendation. WI (2017)
Marco Rossetti, Fabio Stella, Markus Zanker
Contrasting Offline and Online Results when Evaluating Recommendation Algorithms. RecSys (2016)
Marco Rossetti, Fabio Stella, Markus Zanker
Analyzing user reviews in tourism with topic models. J. Inf. Technol. Tour. 16 (1) (2016)
Simone Villa, Fabio Stella
Learning Continuous Time Bayesian Networks in Non-stationary Domains. J. Artif. Intell. Res. 57 (2016)
Maha Amami, Gabriella Pasi, Fabio Stella, Rim Faiz
An LDA-Based Approach to Scientific Paper Recommendation. NLDB (2016)
Dario Baretta, Fabio Sartori, Andrea Greco, Riccardo Melen, Fabio Stella, Letizia Bollini, Marco D'addario, Patrizia Steca
Wearable devices and AI techniques integration to promote physical activity. MobileHCI Adjunct (2016)
Marco Rossetti, Fabio Stella, Longbing Cao, Markus Zanker
Analysing User Reviews in Tourism with Topic Models. ENTER (2015)
Daniele Codecasa, Fabio Stella
Classification and clustering with continuous time Bayesian network models. J. Intell. Inf. Syst. 45 (2) (2015)
Marco Zanoni, Francesca Arcelli Fontana, Fabio Stella
On applying machine learning techniques for design pattern detection. J. Syst. Softw. 103 (2015)
Enzo Acerbi, Teresa Zelante, Vipin Narang, Fabio Stella
Gene network inference using continuous time Bayesian networks: a comparative study and application to Th17 cell differentiation. BMC Bioinform. 15 (2014)
Enzo Acerbi, Fabio Stella
Continuous Time Bayesian Networks for Gene Network Reconstruction: A Comparative Study on Time Course Data. ISBRA (2014)
Daniele Codecasa, Fabio Stella
Learning continuous time Bayesian network classifiers. Int. J. Approx. Reason. 55 (8) (2014)
Daniele Codecasa, Fabio Stella
CTBNCToolkit: Continuous Time Bayesian Network Classifier Toolkit. CoRR (2014)
Remo Pareschi, Marco Rossetti, Fabio Stella
Tracking Hot Topics for the Monitoring of Open-World Processes. SIMPDA (2014)
Marco Rossetti, Remo Pareschi, Fabio Stella, Francesca Arcelli Fontana
Integrating Concepts and Knowledge in Large Content Networks. New Gener. Comput. 32 (3-4) (2014)
Marco Rossetti, Fabio Stella, Markus Zanker
Towards Explaining Latent Factors with Topic Models in Collaborative Recommender Systems. DEXA Workshops (2013)
Daniele Codecasa, Fabio Stella
A Classification Based Scoring Function for Continuous Time Bayesian Network Classifiers. NFMCP (2013)
Gianluigi Viscusi, Federico Cabitza, Andrea Maurino, Fabio Stella
Determining factors in ICT adoption by MSME's in agriculture clusters: An exploratory case study. RCIS (2013)
Domenico Fraccalvieri, Laura Bonati, Fabio Stella
Self Organizing Maps to efficiently cluster and functionally interpret protein conformational ensembles. WIVACE (2013)
Fabio Stella, Y. Amer
Continuous time Bayesian network classifiers. J. Biomed. Informatics 45 (6) (2012)
Eduardo H. Ramírez, Ramón F. Brena, Davide Magatti, Fabio Stella
Topic model validation. Neurocomputing 76 (1) (2012)
Domenico Fraccalvieri, Alessandro Pandini, Fabio Stella, Laura Bonati
Conformational and functional analysis of molecular dynamics trajectories by Self-Organising Maps. BMC Bioinform. 12 (2011)
Eduardo H. Ramírez, Ramón F. Brena, Davide Magatti, Fabio Stella
Probabilistic Metrics for Soft-Clustering and Topic Model Validation. Web Intelligence (2010)
Daniele Barone, Fabio Stella, Carlo Batini
Dependency Discovery in Data Quality. CAiSE (2010)
Enzo Acerbi, Guillermo Pérez, Fabio Stella
Hybrid Syntactic-Semantic Reranking for Parsing Results of ECAs Interactions Using CRFs. IceTAL (2010)
Davide Magatti, Fabio Stella, Marco Faini
A Software System for Topic Extraction and Document Classification. Web Intelligence (2009)
Davide Magatti, Silvia Calegari, Davide Ciucci, Fabio Stella
Automatic Labeling of Topics. ISDA (2009)
Fabio Stella, Vittorio Viganò, Davide Bogni, Matteo Benzoni
An Integrated Forecasting and Regularization Framework for Light Rail Transit Systems. J. Intell. Transp. Syst. 10 (2) (2006)
Alexei A. Gaivoronski, Fabio Stella
Stochastic Nonstationary Optimization for Finding Universal Portfolios. Ann. Oper. Res. 100 (1-4) (2000)
Alexei A. Gaivoronski, Fabio Stella
Stochastic optimization with structured distributions: The case of Bayesian nets. Ann. Oper. Res. 81 (1998)
John J. McKeown, Fabio Stella, Gary Hall
Some numerical aspects of the training problem for feed-forward neural nets. Neural Networks 10 (8) (1997)