Fabrizio Riguzzi

发表

Probabilistic Logic Programming Under the Distribution Semantics

T. Swift, Fabrizio Riguzzi, 2014 .

Applying the Information Bottleneck Approach to SRL : Learning LPAD Parameters

Nicola Di Mauro, Fabrizio Riguzzi, 2010 .

A Hybrid Extensional / Intensional System forLearning Multiple Predicate Learning andNormal Logic

M. Milano, P. Mello, Fabrizio Riguzzi, 1997 .

Learning Three-Valued Logic Programs

E. Lamma, Fabrizio Riguzzi, 1999 .

A Survey of Software Metrics

Fabrizio Riguzzi, 2002 .

1 ITALIAN GEODETIC RESEARCH ACTIVITIES IN THE PERIOD 2007-2011 IAG REPORT

F. Sansò, M. Roggero, A. Vitti, 2011 .

Integrating Extensional and Intensional ILPSystems through

M. Milano, P. Mello, Fabrizio Riguzzi, 1997 .

Exploiting Abduction for Learning from Incomplete Interpretations

P. Mello, E. Lamma, Fabrizio Riguzzi, 2006 .

Editor in Chief of Intelligenza Artificiale

Fabrizio Riguzzi, Fabrizio Riguzzi, 2016 .

A Machine Learning Framework for Multi-Hazard Risk Assessment at the Regional Scale in Earthquake and Flood-Prone Areas

A. Rocchi, Ž. Nikolić, E. Benvenuti, 2022, Applied Sciences.

Probabilistic Inductive Logic Programming

Fabrizio Riguzzi, 2014 .

A Simple Approach to a Multi-Label Classification Problem

Fabrizio Riguzzi, 2005 .

Inducing Specification of Interaction Protocols and Business Processes and Proving their Properties

Evelina Lamma, Fabrizio Riguzzi, Marco Alberti, 2008, Il Milione.

Probabilistic Ontologies in Datalog+/-

Evelina Lamma, Fabrizio Riguzzi, Elena Bellodi, 2012, CILC.

cplint and PITA

Fabrizio Riguzzi, 2011 .

Probabilistic Logic Models for the Lightning Network

Fabrizio Riguzzi, Damiano Azzolini, 2022, Cryptogr..

Membro dell’Editorial Board della rivista Machine Learning and Knowledge Extraction

Fabrizio Riguzzi, Fabrizio Riguzzi, 2017 .

Preface

Fabrizio Riguzzi, Alberto Pettorossi, Marco Gavanelli, 2010, Fundamenta Informaticae.

Abduction in (Probabilistic) Answer Set Programming

Fabrizio Riguzzi, Elena Bellodi, Damiano Azzolini, 2022, CILC.

A Survey of Software Metrics

Fabrizio Riguzzi, 2002 .

Semantics for Hybrid Probabilistic Logic Programs with Function Symbols: Technical Summary

E. Lamma, Fabrizio Riguzzi, Damiano Azzolini, 2022, ICLP Workshops.

A Probabilistic Logic Model of Lightning Network

E. Lamma, Fabrizio Riguzzi, Elena Bellodi, 2021, BIS.

Statistical relational learning for workflow mining

Evelina Lamma, Fabrizio Riguzzi, Elena Bellodi, 2016, Intell. Data Anal..

A History of Probabilistic Inductive Logic Programming

Fabrizio Riguzzi, Elena Bellodi, Riccardo Zese, 2014, Front. Robot. AI.

Lifted Variable Elimination for Probabilistic Logic Programming

Evelina Lamma, Fabrizio Riguzzi, Vítor Santos Costa, 2014, Theory and Practice of Logic Programming.

Structure learning of probabilistic logic programs by searching the clause space

Fabrizio Riguzzi, Elena Bellodi, Fabrizio Riguzzi, 2013, Theory and Practice of Logic Programming.

Italian Machine Learning and Data Mining research: The last years

Fabrizio Riguzzi, Donato Malerba, Davide Bacciu, 2013, Intelligenza Artificiale.

Experimentation of an expectation maximization algorithm for probabilistic logic programs

Fabrizio Riguzzi, Elena Bellodi, Fabrizio Riguzzi, 2012, Intelligenza Artificiale.

Applying the information bottleneck to statistical relational learning

Fabrizio Riguzzi, Nicola Di Mauro, Fabrizio Riguzzi, 2011, Machine Learning.

MCINTYRE: A Monte Carlo Algorithm for Probabilistic Logic Programming

Fabrizio Riguzzi, Fabrizio Riguzzi, 2011, CILC.

Checking Compliance of Execution Traces to Business Rules

Paola Mello, Fabrizio Riguzzi, Federico Chesani, 2008, Business Process Management Workshops.

A logic-based approach to model interaction amongst computees

Evelina Lamma, Paola Mello, Fabrizio Riguzzi, 2003 .

Symbolic DNN-Tuner

E. Lamma, Fabrizio Riguzzi, Michele Fraccaroli, 2021, Machine Learning.

Inductive Logic Programming

Fabrizio Riguzzi, F. Riguzzi, Fabrizio Riguzzi, 2012, Lecture Notes in Computer Science.

A Comparison of ILP Systems on the Sisyphus Dataset

Fabrizio Riguzzi, 2005 .

Identification of natural selection in genomic data with deep convolutional neural network

Fabrizio Riguzzi, Emiliano Trucchi, Giorgio Bertorelle, 2021, BioData Mining.

Vision Inspection with Neural Networks

Evelina Lamma, Fabrizio Riguzzi, Arnaud Nguembang Fadja, 2018, RiCeRcA@AI*IA.

Bandit-based Monte-Carlo structure learning of probabilistic logic programs

Fabrizio Riguzzi, Nicola Di Mauro, Elena Bellodi, 2015, Machine Learning.

EM over Binary Decision Diagrams for Probabilistic Logic Programs

Fabrizio Riguzzi, Elena Bellodi, Fabrizio Riguzzi, 2011, CILC.

A survey of lifted inference approaches for probabilistic logic programming under the distribution semantics

Fabrizio Riguzzi, Giuseppe Cota, Evelina Lamma, 2017, Int. J. Approx. Reason..

Belief revision via Lamarckian evolution

Luís Moniz Pereira, Evelina Lamma, Fabrizio Riguzzi, 2003, New Generation Computing.

Belief Revision by Lamarckian Evolution

Luís Moniz Pereira, Evelina Lamma, Fabrizio Riguzzi, 2001, EvoWorkshops.

Belief Revision by Lamarckian

Moniz Pereira, Fabrizio Riguzzi, Lamma, 2001 .

A Logic Based Approach to Multi-Agent Systems

Evelina Lamma, Fabrizio Riguzzi, Pierangelo Dell'Acqua, 2001 .

A web system for reasoning with probabilistic OWL

Evelina Lamma, Fabrizio Riguzzi, Giuseppe Cota, 2017, Softw. Pract. Exp..

Tableau reasoning for description logics and its extension to probabilities

Evelina Lamma, Fabrizio Riguzzi, Giuseppe Cota, 2018, Annals of Mathematics and Artificial Intelligence.

Probabilistic Hybrid Knowledge Bases Under the Distribution Semantics

Evelina Lamma, Fabrizio Riguzzi, Marco Alberti, 2016, AI*IA.

Probabilistic Description Logics under the distribution semantics

Evelina Lamma, Fabrizio Riguzzi, Elena Bellodi, 2015, Semantic Web.

Semantics and Inference for Probabilistic Description Logics

Evelina Lamma, Fabrizio Riguzzi, Elena Bellodi, 2013, URSW.

Probabilistic Datalog+/- under the Distribution Semantics

Evelina Lamma, Fabrizio Riguzzi, Elena Bellodi, 2012, Description Logics.

Extended semantics and inference for the Independent Choice Logic

Fabrizio Riguzzi, Fabrizio Riguzzi, 2009, Log. J. IGPL.

Well–definedness and efficient inference for probabilistic logic programming under the distribution semantics

Fabrizio Riguzzi, Theresa Swift, T. Swift, 2011, Theory and Practice of Logic Programming.

Lifted discriminative learning of probabilistic logic programs

Fabrizio Riguzzi, Arnaud Nguembang Fadja, Fabrizio Riguzzi, 2018, Machine Learning.

Parameter Learning for Probabilistic Ontologies

Evelina Lamma, Fabrizio Riguzzi, Elena Bellodi, 2013, RR.

BUNDLE: A Reasoner for Probabilistic Ontologies

Evelina Lamma, Fabrizio Riguzzi, Elena Bellodi, 2013, RR.

Epistemic and Statistical Probabilistic Ontologies

Evelina Lamma, Fabrizio Riguzzi, Elena Bellodi, 2012, URSW.

Parameter and Structure Learning Algorithms for Statistical Relational Learning

Fabrizio Riguzzi, Elena Bellodi, Fabrizio Riguzzi, 2012, DC@AI*IA.

Semantics and Inference for Probabilistic Ontologies

Evelina Lamma, Fabrizio Riguzzi, Elena Bellodi, 2012, PAI.

A Distribution Semantics for Probabilistic Ontologies

Evelina Lamma, Fabrizio Riguzzi, Elena Bellodi, 2011, URSW.

Inference with Logic Programs with Annotated Disjunctions under the Well Founded Semantics

Fabrizio Riguzzi, Fabrizio Riguzzi, 2008, ICLP.

Learning specifications of interaction protocols and business processes and proving their properties

Evelina Lamma, Fabrizio Riguzzi, Marco Alberti, 2011, Intelligenza Artificiale.

Incremental Declarative Process Mining

Evelina Lamma, Fabrizio Riguzzi, Sergio Storari, 2010, Smart Information and Knowledge Management.

Exploiting Inductive Logic Programming Techniques for Declarative Process Mining

Evelina Lamma, Paola Mello, Fabrizio Riguzzi, 2009, Trans. Petri Nets Other Model. Concurr..

Abductive concept learning

Fabrizio Riguzzi, Antonis C. Kakas, A. Kakas, 2000, New Generation Computing.

Inducing Declarative Logic-Based Models from Labeled Traces

Evelina Lamma, Paola Mello, Fabrizio Riguzzi, 2007, BPM.

Integrating Abduction and Induction in the Learning from Interpretation Setting

P. Mello, E. Lamma, Fabrizio Riguzzi, 2005 .

Inductive Logic Programming

Fabrizio Riguzzi, F. Riguzzi, Fabrizio Riguzzi, 1998, Lecture Notes in Computer Science.

Learning the Structure of Probabilistic Logic Programs

Fabrizio Riguzzi, Elena Bellodi, Fabrizio Riguzzi, 2011, ILP.

Learning Logic Programs with Annotated Disjunctions

Fabrizio Riguzzi, Fabrizio Riguzzi, 2004, ILP.

Artificial intelligence techniques for monitoring dangerous infections

Evelina Lamma, Paola Mello, Fabrizio Riguzzi, 2006, IEEE Transactions on Information Technology in Biomedicine.

Strategies in Combined Learning via Logic Programs

Luís Moniz Pereira, Evelina Lamma, Fabrizio Riguzzi, 2004, Machine Learning.

Learning in a Three-valued Setting

Evelina Lamma, Fabrizio Riguzzi, E. Lamma, 1998 .

Adopting an Object-Oriented Data Model in Inductive Logic Programming

Fabrizio Riguzzi, Andrea Omicini, Michela Milano, 1999, FLAIRS.

Exploiting association and correlation rules parameters for learning Bayesian networks

Evelina Lamma, Fabrizio Riguzzi, Sergio Storari, 2009, Intell. Data Anal..

Algorithms for Efficiently and Effectively Using Background Knowledge in Tertius

Fabrizio Riguzzi, Marco Gavanelli, Peter Flach, 2006 .

Integrating Induction and Abduction in Logic Programming

Evelina Lamma, Paola Mello, Fabrizio Riguzzi, 1999, Inf. Sci..

From the global scale to the Mediterranean plate kinematics

Fabrizio Riguzzi, 2008 .

Reasoning with Probabilistic Ontologies

Evelina Lamma, Fabrizio Riguzzi, Elena Bellodi, 2015, IJCAI.

Quantum Weighted Model Counting

Fabrizio Riguzzi, 2019, ECAI.

A semantics for Hybrid Probabilistic Logic programs with function symbols

Evelina Lamma, Fabrizio Riguzzi, Damiano Azzolini, 2021, Artif. Intell..

Probabilistic Logical Inference on the Web

Fabrizio Riguzzi, Marco Alberti, Giuseppe Cota, 2016, AI*IA.

cplint on SWISH: Probabilistic Logical Inference with a Web Browser

Fabrizio Riguzzi, Marco Alberti, Giuseppe Cota, 2017, Intelligenza Artificiale.

Probabilistic Logic Programming in Action

Fabrizio Riguzzi, Arnaud Nguembang Fadja, Fabrizio Riguzzi, 2015, BIRS-IMLKE.

Automatic Differentiation in Prolog

Birthe van den Berg, T. Schrijvers, Fabrizio Riguzzi, 2023, Theory and Practice of Logic Programming.

Abduction with probabilistic logic programming under the distribution semantics

S. Ferilli, Fabrizio Riguzzi, Elena Bellodi, 2021, Int. J. Approx. Reason..

Exploiting Association and Correlation Rules - Parameters for Improving the K2 Algorithm

Evelina Lamma, Fabrizio Riguzzi, Sergio Storari, 2004, ECAI.

Discovering validation rules from microbiological data

Evelina Lamma, Paola Mello, Fabrizio Riguzzi, 2003, New Generation Computing.

Combining APRIORI and Bootstrap Techniques for Marker Analysis

C. Scapoli, G. Gamberoni, E. Lamma, 2007 .

Marker Analysis with APRIORI-based Algorithms

Evelina Lamma, Fabrizio Riguzzi, Sergio Storari, 2006 .

Improving the K2 Algorithm Using Association Rule Parameters

Evelina Lamma, Fabrizio Riguzzi, Sergio Storari, 2006 .

A System for Measuring Function Points from Specifications

P. Mello, E. Lamma, Fabrizio Riguzzi, 2008 .

Specification of the Application SuperSport with ER-DFD

Fabrizio Riguzzi, Fabrizio Riguzzi, 2003 .

Approximate Inference in Probabilistic Answer Set Programming for Statistical Probabilities

Fabrizio Riguzzi, Elena Bellodi, Damiano Azzolini, 2022, AI*IA.

Probabilistic Declarative Process Mining

Evelina Lamma, Fabrizio Riguzzi, Elena Bellodi, 2010, KSEM.

Applying Inductive Logic Programming to Process Mining

Evelina Lamma, Paola Mello, Fabrizio Riguzzi, 2007, ILP.

Deliverable D14: Experiments with animated societies of computees

A. Bracciali, A. Ciampolini, P. Mello, 2005 .

Data Selection and Feature Engineering for the Application of Machine Learning to the Prediction of Gas Turbine Trip

M. Venturini, Fabrizio Riguzzi, G. Bechini, 2021, Volume 8: Oil and Gas Applications; Steam Turbine.

Prediction of Gas Turbine Trip: a Novel Methodology Based on Random Forest Models

M. Venturini, Fabrizio Riguzzi, G. Bechini, 2021, Volume 8: Oil and Gas Applications; Steam Turbine.

Structured Methodology for Clustering Gas Turbine Transients by Means of Multivariate Time Series

M. Venturini, Fabrizio Riguzzi, G. Bechini, 2021, Journal of Engineering for Gas Turbines and Power.

Foundations of Probabilistic Logic Programming

Fabrizio Riguzzi, Fabrizio Riguzzi, 2018 .

Studying Transaction Fees in the Bitcoin Blockchain with Probabilistic Logic Programming

Evelina Lamma, Fabrizio Riguzzi, Damiano Azzolini, 2019, Inf..

Analyzing Transaction Fees with Probabilistic Logic Programming

Fabrizio Riguzzi, Evelina Lamma, Damiano Azzolini, 2019, BIS.

Modeling Smart Contracts with Probabilistic Logic Programming

Fabrizio Riguzzi, Evelina Lamma, Damiano Azzolini, 2020, BIS.

Learning hierarchical probabilistic logic programs

Evelina Lamma, Fabrizio Riguzzi, Arnaud Nguembang Fadja, 2021, Machine Learning.

Agents Learning in a Three-Valued Logical Setting

Evelina Lamma, Fabrizio Riguzzi, E. Lamma, 2007 .

Introduzione all'Intelligenza Artificiale pdf

Fabrizio Riguzzi, Fabrizio Riguzzi, 2015, ArXiv.

MAP Inference for Probabilistic Logic Programming

M. Alberti, Fabrizio Riguzzi, Elena Bellodi, 2020, Theory and Practice of Logic Programming.

Causal inference in cplint

Fabrizio Riguzzi, Giuseppe Cota, Elena Bellodi, 2017, Int. J. Approx. Reason..

Structured Methodology for Clustering Gas Turbine Transients by Means of Multi-Variate Time Series

M. Venturini, Fabrizio Riguzzi, G. Bechini, 2020 .

Probabilistic Constraint Logic Theories

Evelina Lamma, Fabrizio Riguzzi, Marco Alberti, 2016, PLP@ILP.

Bayesian Networks Learning for Gene Expression Datasets

Evelina Lamma, Fabrizio Riguzzi, Sergio Storari, 2005, IDA.

Improving the SLA Algorithm Using Association Rules

Evelina Lamma, Fabrizio Riguzzi, Sergio Storari, 2003, AI*IA.

Probabilistic Description Logics under the distribution semantics

E. Lamma, Fabrizio Riguzzi, Elena Bellodi, 2015, Semantic Web.

Learning Multiple Predicates

Evelina Lamma, Fabrizio Riguzzi, Antonis C. Kakas, 1998, AIMSA.

A System for Abductive Learning of Logic Programs

Evelina Lamma, Paola Mello, Fabrizio Riguzzi, 1997, LPKR.

Learning with Abduction

Fabrizio Riguzzi, Antonis C. Kakas, A. Kakas, 1997, ILP.

Dischargeable Obligations in Abductive Logic Programming

Evelina Lamma, Fabrizio Riguzzi, Marco Alberti, 2017, RuleML+RR.

A Top Down Interpreter for LPAD and CP-Logic

Fabrizio Riguzzi, Fabrizio Riguzzi, 2007, AI*IA.

The distribution semantics for normal programs with function symbols

Fabrizio Riguzzi, Fabrizio Riguzzi, 2016, Int. J. Approx. Reason..

Introducing Abduction into (Extensional) Inductive Logic Programming Systems

Evelina Lamma, Paola Mello, Fabrizio Riguzzi, 1997, AI*IA.

An Expert System for Microbiological Data Validation and Surveillance

Evelina Lamma, Paola Mello, Fabrizio Riguzzi, 2001, ISMDA.

A System for Monitoring Nosocomial Infections

Evelina Lamma, Paola Mello, Fabrizio Riguzzi, 2000, ISMDA.

Constraint and Optimization techniques for supporting Policy Making

M. Milano, M. Gavanelli, Fabrizio Riguzzi, 2012, ISAIM.

Using SWISH to Realize Interactive Web-based Tutorials for Logic-based Languages

Fabrizio Riguzzi, Jan Wielemaker, Torbjörn Lager, 2018, Theory and Practice of Logic Programming.

Abductive logic programming for Datalog +/- ontologies

Evelina Lamma, Fabrizio Riguzzi, Marco Gavanelli, 2015, CILC.

The PITA system: Tabling and answer subsumption for reasoning under uncertainty

T. Swift, Fabrizio Riguzzi, 2011, Theory and Practice of Logic Programming.

Symbolic DNN-Tuner

E. Lamma, Fabrizio Riguzzi, Michele Fraccaroli, 2021, Machine Learning.