Marco Muselli

Orcid: 0000-0002-9999-2331

According to our database1, Marco Muselli authored at least 70 papers between 1992 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2024
Overcoming Therapeutic Inertia in Type 2 Diabetes: Exploring Machine Learning-Based Scenario Simulation for Improving Short-Term Glycemic Control.
Mach. Learn. Knowl. Extr., March, 2024

A transparent machine learning algorithm uncovers HbA1c patterns associated with therapeutic inertia in patients with type 2 diabetes and failure of metformin monotherapy.
Int. J. Medical Informatics, 2024

Rulex Platform: leveraging domain knowledge and data-driven rules to support decisions in the fintech sector through eXplainable AI models.
Proceedings of the Joint Proceedings of the xAI 2024 Late-breaking Work, 2024

2023
Trustworthy artificial intelligence classification-based equivalent bandwidth control.
Comput. Commun., September, 2023

Optimizing Water Distribution through Explainable AI and Rule-Based Control.
Comput., June, 2023

CONFIDERAI: a novel CONFormal Interpretable-by-Design score function for Explainable and Reliable Artificial Intelligence.
CoRR, 2023

Weighted Mutual Information for Out-Of-Distribution Detection.
Proceedings of the Explainable Artificial Intelligence, 2023

CONFIDERAI: CONFormal Interpretable-by-Design score function for Explainable and Reliable Artificial Intelligence.
Proceedings of the Conformal and Probabilistic Prediction with Applications, 2023

2022
VAMPIRE: vectorized automated ML pre-processing and post-processing framework for edge applications.
Computing, 2022

A Novel Rule-Based Modeling and Control Approach for the Optimization of Complex Water Distribution Networks.
Proceedings of the Advances in System-Integrated Intelligence, 2022

2021
Porting Rulex Software to the Raspberry Pi for Machine Learning Applications on the Edge.
Sensors, 2021

2020
A Unified View to Machine Learning and Control for Measurement-based Equivalent Bandwidth.
Proceedings of the 16th International Conference on the Design of Reliable Communication Networks, 2020

Porting Rulex Machine Learning Software to the Raspberry Pi as an Edge Computing Device.
Proceedings of the Applications in Electronics Pervading Industry, Environment and Society, 2020

2019
Unsupervised learning and rule extraction for Domain Name Server tunneling detection.
Internet Technol. Lett., 2019

Performance validation of vehicle platooning through intelligible analytics.
IET Cyper-Phys. Syst.: Theory & Appl., 2019

Analyzing gene expression data for pediatric and adult cancer diagnosis using logic learning machine and standard supervised methods.
BMC Bioinform., 2019

Accellerating PRISM Validation of Vehicle Platooning Through Machine Learning.
Proceedings of the 4th International Conference on System Reliability and Safety, 2019

Achieving Zero Collision Probability in Vehicle Platooning under Cyber Attacks via Machine Learning.
Proceedings of the 4th International Conference on System Reliability and Safety, 2019

2018
Logic Learning Machine and standard supervised methods for Hodgkin's lymphoma prognosis using gene expression data and clinical variables.
Health Informatics J., 2018

Identification of safety regions in vehicle platooning via machine learning.
Proceedings of the 14th IEEE International Workshop on Factory Communication Systems, 2018

2015
Differential diagnosis of pleural mesothelioma using Logic Learning Machine.
BMC Bioinform., 2015

2014
Use of Attribute Driven Incremental Discretization and Logic Learning Machine to build a prognostic classifier for neuroblastoma patients.
BMC Bioinform., 2014

2013
Logic Learning Machine creates explicit and stable rules stratifying neuroblastoma patients.
BMC Bioinform., 2013

Combining Not-Proper ROC Curves and Hierarchical Clustering to Detect Differentially Expressed Genes in Microarray Experiments.
Proceedings of the Computational Intelligence Methods for Bioinformatics and Biostatistics, 2013

2011
Coupling Logical Analysis of Data and Shadow Clustering for Partially Defined Positive Boolean Function Reconstruction.
IEEE Trans. Knowl. Data Eng., 2011

A Mathematical Model for the Validation of Gene Selection Methods.
IEEE ACM Trans. Comput. Biol. Bioinform., 2011

Implementing reliable learning through Reliable Support Vector Machines.
Proceedings of the IEEE Symposium on Foundations of Computational Intelligence, 2011

2010
Efficient global maximum likelihood estimation through kernel methods.
Neural Networks, 2010

Functional Optimization Through Semilocal Approximate Minimization.
Oper. Res., 2010

Switching Neural Network: An application to Regression Problems.
Proceedings of the Neural Nets WIRN10, 2010

Maximizing pattern separation in discretizing continuous features for classification purposes.
Proceedings of the International Joint Conference on Neural Networks, 2010

2009
Efficient Constructive Techniques for Training Switching Neural Networks.
Proceedings of the Constructive Neural Networks, 2009

Evaluating switching neural networks through artificial and real gene expression data.
Artif. Intell. Medicine, 2009

2008
Deterministic Learning for Maximum-Likelihood Estimation Through Neural Networks.
IEEE Trans. Neural Networks, 2008

Gene expression modeling through positive boolean functions.
Int. J. Approx. Reason., 2008

Not proper ROC curves as new tool for the analysis of differentially expressed genes in microarray experiments.
BMC Bioinform., 2008

A Constructive Technique Based on Linear Programming for Training Switching Neural Networks.
Proceedings of the Artificial Neural Networks, 2008

A Multivariate Algorithm for Gene Selection Based on the Nearest Neighbor Probability.
Proceedings of the Computational Intelligence Methods for Bioinformatics and Biostatistics, 2008

2007
Network Reliability Assessment through Empirical Models Using a Machine Learning Approach.
Proceedings of the Intelligence in Reliability Engineering: New Metaheuristics, 2007

Efficient sampling in approximate dynamic programming algorithms.
Comput. Optim. Appl., 2007

Evaluating Switching Neural Networks for Gene Selection.
Proceedings of the Applications of Fuzzy Sets Theory, 2007

Reliable Learning: A Theoretical Framework.
Proceedings of the Knowledge-Based Intelligent Information and Engineering Systems, 2007

2005
Approximate multi-state reliability expressions using a new machine learning technique.
Reliab. Eng. Syst. Saf., 2005

Switching Neural Networks: A New Connectionist Model for Classification.
Proceedings of the Neural Nets, 16th Italian Workshop on Neural Nets, 2005

Approximation Properties of Positive Boolean Functions.
Proceedings of the Neural Nets, 16th Italian Workshop on Neural Nets, 2005

Biological Specifications for a Synthetic Gene Expression Data Generation Model.
Proceedings of the Fuzzy Logic and Applications, 6th International Workshop, 2005

Reconstructing positive Boolean functions with shadow clustering.
Proceedings of the 2005 European Conference on Circuit Theory and Design, 2005

2004
Deterministic design for neural network learning: an approach based on discrepancy.
IEEE Trans. Neural Networks, 2004

Empirical models based on machine learning techniques for determining approximate reliability expressions.
Reliab. Eng. Syst. Saf., 2004

Cancer recognition with bagged ensembles of support vector machines.
Neurocomputing, 2004

Consistency of Empirical Risk Minimization for Unbounded Loss Functions.
Proceedings of the Biological and Artificial Intelligence Environments, 2004

Assessing the Reliability of Communication Networks Through Maghine Learning Techniques.
Proceedings of the Biological and Artificial Intelligence Environments, 2004

2003
A clustering technique for the identification of piecewise affine systems.
Autom., 2003

A Deterministic Learning Approch Based on Discrepancy.
Proceedings of the Neural Nets, 14th Italian Workshop on Neural Nets, 2003

Single-Linkage Clustering for Optimal Classification in Piecewise Affine Regression.
Proceedings of the IFAC Conference on Analysis and Design of Hybrid Systems, 2003

2002
Binary Rule Generation via Hamming Clustering.
IEEE Trans. Knowl. Data Eng., 2002

A New Learning Method for Piecewise Linear Regression.
Proceedings of the Artificial Neural Networks, 2002

2001
A Learning Algorithm for Piecewise Linear Regression.
Proceedings of the 12th Italian Workshop on Neural Nets, 2001

Support Vector Machines for uncertainty region detection.
Proceedings of the 12th Italian Workshop on Neural Nets, 2001

Detecting uncertainty regions for characterizing classification problems.
Proceedings of the 12th Italian Workshop on Neural Nets, 2001

Identification of piecewise affine and hybrid systems.
Proceedings of the American Control Conference, 2001

2000
Predicting the Generalization Ability of Neural Networks Resembling the Nearest-Neighbor Algorithm.
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000

1999
Hamming Clustering: A New Approach to Rule Extraction.
Proceedings of the Third ICSC Symposia on Intelligent Industrial Automation (IIA'99) and Soft Computing (SOCO'99), 1999

1997
On convergence properties of pocket algorithm.
IEEE Trans. Neural Networks, 1997

A Theoretical Approach to Restart in Global Optimization.
J. Glob. Optim., 1997

1996
Hamming-Clustering method for signals prediction in 5' and 3' regions of eukaryotic genes.
Comput. Appl. Biosci., 1996

Optimality of Pocket Algorithm.
Proceedings of the Artificial Neural Networks, 1996

1995
On sequential construction of binary neural networks.
IEEE Trans. Neural Networks, 1995

Is Pocket algorithm optimal?
Proceedings of the Computational Learning Theory, Second European Conference, 1995

1992
Global Optimization of Functions with the Interval Genetic Algorithm.
Complex Syst., 1992


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