Riccardo Guidotti – författare

This book constitutes revised selected papers from two workshops held at the 18th European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2018, in Dublin, Ireland, in September 2018, namely:

MIDAS 2018 – Third Workshop on Mining Data for Financial Applications andPAP 2018 – Second International Workshop on Personal Analytics and Privacy.

The 12 papers presented in this volume were carefully reviewed and selected from a total of 17 submissions.

This book constitutes the refereed proceedings of the workshops which complemented the 23rd Symposium on Formal Methods, FM 2019, held in Porto, Portugal, in October 2019. This volume presents the papers that have been accepted for the following workshops: Third Workshop on Practical Formal Verification for Software Dependability, AFFORD 2019; 8th International Symposium From Data to Models and Back, DataMod 2019; First Formal Methods for Autonomous Systems Workshop, FMAS 2019; First Workshop on Formal Methods for Blockchains, FMBC 2019; 8th International Workshop on Formal Methods for Interactive Systems, FMIS 2019; First History of Formal Methods Workshop, HFM 2019; 8th International Workshop on Numerical and Symbolic Abstract Domains, NSAD 2019; 9th International Workshop on Open Community Approaches to Education, Research and Technology, OpenCERT 2019; 17th Overture Workshop, Overture 2019; 19th Refinement Workshop, Refine 2019; First International Workshop on Reversibility in Programming, Languages, and Automata, RPLA 2019; 10th International Workshop on Static Analysis and Systems Biology, SASB 2019; and the 10th Workshop on Tools for Automatic Program Analysis, TAPAS 2019.

This book constitutes the refereed proceedings of the workshops which complemented the 23rd Symposium on Formal Methods, FM 2019, held in Porto, Portugal, in October 2019. This volume presents the papers that have been accepted for the following workshops: Third Workshop on Practical Formal Verification for Software Dependability, AFFORD 2019; 8th International Symposium From Data to Models and Back, DataMod 2019; First Formal Methods for Autonomous Systems Workshop, FMAS 2019; First Workshop on Formal Methods for Blockchains, FMBC 2019; 8th International Workshop on Formal Methods for Interactive Systems, FMIS 2019; First History of Formal Methods Workshop, HFM 2019; 8th International Workshop on Numerical and Symbolic Abstract Domains, NSAD 2019; 9th International Workshop on Open Community Approaches to Education, Research and Technology, OpenCERT 2019; 17th Overture Workshop, Overture 2019; 19th Refinement Workshop, Refine 2019; First International Workshop on Reversibility in Programming, Languages, and Automata, RPLA 2019; 10th International Workshop on Static Analysis and Systems Biology, SASB 2019; and the 10th Workshop on Tools for Automatic Program Analysis, TAPAS 2019.

The two-volume set LNAI 15243 + 15244 constitutes the proceedings of the 27th International Conference on Discovery Science, DS 2024, which took place in Pisa, Italy, during October 14-16, 2024.

The 53 full papers presented in the proceedings were carefully reviewed and selected from 121 submissions. They were organized in topical sections as follows: 

Part I: LLM, Text Analytics, and Ethical Aspects of AI; Natural Language Processing, Sequential Data and Science Discovery; Data-Driven Science Discovery Methodologies; Graph Neural Network, Graph Theory, Unsupervised Learning and Regression; 

Part II: Tree-Based Models and Causal Discovery; Security and Anomaly Detection; Computer Vision and Explainable AI; Classification Models; SoBigData++: City for Citizens and Explainable AI; SoBigData++: Societal Debates and Misinformation Analysis.

The two-volume set LNAI 15243 + 15244 constitutes the proceedings of the 27th International Conference on Discovery Science, DS 2024, which took place in Pisa, Italy, during October 14-16, 2024.

The 53 full papers presented in the proceedings were carefully reviewed and selected from 121 submissions. They were organized in topical sections as follows: 

Part I: LLM, Text Analytics, and Ethical Aspects of AI; Natural Language Processing, Sequential Data and Science Discovery; Data-Driven Science Discovery Methodologies; Graph Neural Network, Graph Theory, Unsupervised Learning and Regression; 

Part II: Tree-Based Models and Causal Discovery; Security and Anomaly Detection; Computer Vision and Explainable AI; Classification Models; SoBigData++: City for Citizens and Explainable AI; SoBigData++: Societal Debates and Misinformation Analysis.