Andrea Passerini

Orcid: 0000-0002-2765-5395

Affiliations:
  • University of Trento, Italy


According to our database1, Andrea Passerini authored at least 156 papers between 2001 and 2024.

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Bibliography

2024
Glitter or gold? Deriving structured insights from sustainability reports via large language models.
EPJ Data Sci., December, 2024

Enhancing SMT-based Weighted Model Integration by structure awareness.
Artif. Intell., March, 2024

Personalized Algorithmic Recourse with Preference Elicitation.
Trans. Mach. Learn. Res., 2024

Personalized bundle recommendation using preference elicitation and the Choquet integral.
Frontiers Artif. Intell., 2024

Time Can Invalidate Algorithmic Recourse.
CoRR, 2024

xAI-Drop: Don't Use What You Cannot Explain.
CoRR, 2024

Perks and Pitfalls of Faithfulness in Regular, Self-Explainable and Domain Invariant GNNs.
CoRR, 2024

A Benchmark Suite for Systematically Evaluating Reasoning Shortcuts.
CoRR, 2024

Semantic Loss Functions for Neuro-Symbolic Structured Prediction.
CoRR, 2024

Exploiting Preference Elicitation in Interactive and User-centered Algorithmic Recourse: An Initial Exploration.
CoRR, 2024

Unveiling LLMs: The Evolution of Latent Representations in a Temporal Knowledge Graph.
CoRR, 2024

Learning To Guide Human Decision Makers With Vision-Language Models.
CoRR, 2024

BEARS Make Neuro-Symbolic Models Aware of their Reasoning Shortcuts.
CoRR, 2024

A Unified Framework for Probabilistic Verification of AI Systems via Weighted Model Integration.
CoRR, 2024

Preference Elicitation in Interactive and User-centered Algorithmic Recourse: an Initial Exploration.
Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization, 2024

Can LLMs Correct Physicians, Yet? Investigating Effective Interaction Methods in the Medical Domain.
Proceedings of the 6th Clinical Natural Language Processing Workshop, 2024

2023
Adaptation of student behavioural routines during Covid-19: a multimodal approach.
EPJ Data Sci., December, 2023

Interpretability Is in the Mind of the Beholder: A Causal Framework for Human-Interpretable Representation Learning.
Entropy, December, 2023

Synthesizing explainable counterfactual policies for algorithmic recourse with program synthesis.
Mach. Learn., April, 2023

Semantic Loss Functions for Neuro-Symbolic Structured Prediction.
Proceedings of the Compendium of Neurosymbolic Artificial Intelligence, 2023

Graph Neural Networks for Temporal Graphs: State of the Art, Open Challenges, and Opportunities.
Trans. Mach. Learn. Res., 2023

Learning to Guide Human Experts via Personalized Large Language Models.
CoRR, 2023

Interval Logic Tensor Networks.
CoRR, 2023

Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcuts.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Neuro-Symbolic Reasoning Shortcuts: Mitigation Strategies and their Limitations.
Proceedings of the 17th International Workshop on Neural-Symbolic Learning and Reasoning, 2023

Generalized Reasoning With Graph Neural Networks by Relational Bayesian Network Encodings.
Proceedings of the Learning on Graphs Conference, 27-30 November 2023, Virtual Event., 2023

A Simple Latent Variable Model for Graph Learning and Inference.
Proceedings of the Learning on Graphs Conference, 27-30 November 2023, Virtual Event., 2023

Meta-Path Learning for Multi-Relational Graph Neural Networks.
Proceedings of the Learning on Graphs Conference, 27-30 November 2023, Virtual Event., 2023

Neuro-Symbolic Continual Learning: Knowledge, Reasoning Shortcuts and Concept Rehearsal.
Proceedings of the International Conference on Machine Learning, 2023

Concept-level Debugging of Part-Prototype Networks.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Global Explainability of GNNs via Logic Combination of Learned Concepts.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Value-Based Hybrid Intelligence.
Proceedings of the HHAI 2023: Augmenting Human Intellect, 2023

Value-Aware Active Learning.
Proceedings of the HHAI 2023: Augmenting Human Intellect, 2023

Egocentric Hierarchical Visual Semantics.
Proceedings of the HHAI 2023: Augmenting Human Intellect, 2023

Environmentally-Aware Bundle Recommendation Using the Choquet Integral.
Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

A Neuro-Symbolic Approach for Non-Intrusive Load Monitoring.
Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

2022
An efficient procedure for mining egocentric temporal motifs.
Data Min. Knowl. Discov., 2022

Human-in-the-loop handling of knowledge drift.
Data Min. Knowl. Discov., 2022

Explaining the Explainers in Graph Neural Networks: a Comparative Study.
CoRR, 2022

Rethinking and Recomputing the Value of ML Models.
CoRR, 2022

Concept-level Debugging of Part-Prototype Networks.
CoRR, 2022

GlanceNets: Interpretabile, Leak-proof Concept-based Models.
CoRR, 2022

Generating personalized counterfactual interventions for algorithmic recourse by eliciting user preferences.
CoRR, 2022

Machine Learning for Combinatorial Optimisation of Partially-Specified Problems: Regret Minimisation as a Unifying Lens.
CoRR, 2022

Lifelong Personal Context Recognition.
CoRR, 2022

Neighbourhood matching creates realistic surrogate temporal networks.
CoRR, 2022

Skeptical Learning - An Algorithm and a Platform for Dealing with Mislabeling in Personal Context Recognition.
Algorithms, 2022

SMT-based weighted model integration with structure awareness.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

A Neuro-Symbolic Approach for Real-World Event Recognition from Weak Supervision.
Proceedings of the 29th International Symposium on Temporal Representation and Reasoning, 2022

GlanceNets: Interpretable, Leak-proof Concept-based Models.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Generalising via Meta-examples for Continual Learning in the Wild.
Proceedings of the Machine Learning, Optimization, and Data Science, 2022

Catastrophic Forgetting in Continual Concept Bottleneck Models.
Proceedings of the Image Analysis and Processing. ICIAP 2022 Workshops, 2022

2021
Towards Visual Semantics.
SN Comput. Sci., 2021

Give more data, awareness and control to individual citizens, and they will help COVID-19 containment.
Ethics Inf. Technol., 2021

Putting human behavior predictability in context.
EPJ Data Sci., 2021

The Science of Rejection: A Research Area for Human Computation.
CoRR, 2021

Toward a Unified Framework for Debugging Gray-box Models.
CoRR, 2021

Learning compositional programs with arguments and sampling.
CoRR, 2021

A review and experimental analysis of active learning over crowdsourced data.
Artif. Intell. Rev., 2021

Learning Modulo Theories for constructive preference elicitation.
Artif. Intell., 2021

A Neuro-Symbolic Approach to Structured Event Recognition.
Proceedings of the 28th International Symposium on Temporal Representation and Reasoning, 2021

Interactive Label Cleaning with Example-based Explanations.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Neuro-Symbolic Constraint Programming for Structured Prediction.
Proceedings of the 15th International Workshop on Neural-Symbolic Learning and Reasoning as part of the 1st International Joint Conference on Learning & Reasoning (IJCLR 2021), 2021

Co-creating Platformer Levels with Constrained Adversarial Networks.
Proceedings of the Joint Proceedings of the ACM IUI 2021 Workshops co-located with 26th ACM Conference on Intelligent User Interfaces (ACM IUI 2021), 2021

Learning Aggregation Functions.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Hybrid Probabilistic Inference with Logical and Algebraic Constraints: a Survey.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

2020
Deep Learning for Classification and Localization of COVID-19 Markers in Point-of-Care Lung Ultrasound.
IEEE Trans. Medical Imaging, 2020

Dealing with Mislabeling via Interactive Machine Learning.
Künstliche Intell., 2020

Few-Shot Unsupervised Continual Learning through Meta-Examples.
CoRR, 2020

Give more data, awareness and control to individual citizens, and they will help COVID-19 containment.
CoRR, 2020

Efficient Generation of Structured Objects with Constrained Adversarial Networks.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning in the Wild with Incremental Skeptical Gaussian Processes.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Continual Egocentric Object Recognition.
Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

Learning Weighted Model Integration Distributions.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
A Big Data and machine learning approach for network monitoring and security.
Secur. Priv., 2019

Fixing Mislabeling by Human Annotators Leveraging Conflict Resolution and Prior Knowledge.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2019

Special issue: Selected and revised papers from the 17th International Conference of the Italian Association for Artificial Intelligence.
Intelligenza Artificiale, 2019

Counts-of-counts similarity for prediction and search in relational data.
Data Min. Knowl. Discov., 2019

Combining learning and constraints for genome-wide protein annotation.
BMC Bioinform., 2019

Advanced SMT techniques for weighted model integration.
Artif. Intell., 2019

The pywmi Framework and Toolbox for Probabilistic Inference using Weighted Model Integration.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

2018
No more ready-made deals: constructive recommendation for telco service bundling.
Proceedings of the 12th ACM Conference on Recommender Systems, 2018

Automating Layout Synthesis with Constructive Preference Elicitation.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

Learning SMT(LRA) Constraints using SMT Solvers.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Pyconstruct: Constraint Programming Meets Structured Prediction.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Learning Constraints From Examples.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Constructive Preference Elicitation Over Hybrid Combinatorial Spaces.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Decomposition Strategies for Constructive Preference Elicitation.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Constructive Preference Elicitation.
Frontiers Robotics AI, 2017

Structured learning modulo theories.
Artif. Intell., 2017

Introduction to the special issue on Combining Constraint Solving with Mining and Learning.
Artif. Intell., 2017

Efficient Weighted Model Integration via SMT-Based Predicate Abstraction.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Constructive Preference Elicitation for Multiple Users with Setwise Max-margin.
Proceedings of the Algorithmic Decision Theory - 5th International Conference, 2017

Coactive Critiquing: Elicitation of Preferences and Features.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Learning Modulo Theories.
Proceedings of the Data Mining and Constraint Programming, 2016

Guest editors' introduction to the EcmlPkdd 2016 journal track special issue of Machine Learning.
Mach. Learn., 2016

RNAcommender: genome-wide recommendation of RNA-protein interactions.
Bioinform., 2016

Constructive Preference Elicitation by Setwise Max-Margin Learning.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Hashing-Based Approximate Probabilistic Inference in Hybrid Domains: An Abridged Report.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Classtering: Joint Classification and Clustering with Mixture of Factor Analysers.
Proceedings of the ECAI 2016 - 22nd European Conference on Artificial Intelligence, 29 August-2 September 2016, The Hague, The Netherlands, 2016

Component Caching in Hybrid Domains with Piecewise Polynomial Densities.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Learning Modulo Theories for preference elicitation in hybrid domains.
CoRR, 2015

Hashing-Based Approximate Probabilistic Inference in Hybrid Domains.
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Bootstrapping Domain Ontologies from Wikipedia: A Uniform Approach.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Probabilistic Inference in Hybrid Domains by Weighted Model Integration.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

2014
Active Learning of Pareto Fronts.
IEEE Trans. Neural Networks Learn. Syst., 2014

Improving Activity Recognitionby Segmental Pattern Mining.
IEEE Trans. Knowl. Data Eng., 2014

Hybrid SRL with Optimization Modulo Theories.
CoRR, 2014

Joint probabilistic-logical refinement of multiple protein feature predictors.
BMC Bioinform., 2014

Improved multi-level protein¿protein interaction prediction with semantic-based regularization.
BMC Bioinform., 2014

Predicting virus mutations through statistical relational learning.
BMC Bioinform., 2014

2013
Kernel Methods for Structured Data.
Proceedings of the Handbook on Neural Information Processing, 2013

Type Extension Trees for feature construction and learning in relational domains.
Artif. Intell., 2013

Ego-centric Graphlets for Personality and Affective States Recognition.
Proceedings of the International Conference on Social Computing, SocialCom 2013, 2013

ScienScan - An Efficient Visualization and Browsing Tool for Academic Search.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

A Fully Unsupervised Approach to Activity Discovery.
Proceedings of the Human Behavior Understanding - 4th International Workshop, 2013

Navigating the topical structure of academic search results via the Wikipedia category network.
Proceedings of the 22nd ACM International Conference on Information and Knowledge Management, 2013

2012
Predicting Metal-Binding Sites from Protein Sequence.
IEEE ACM Trans. Comput. Biol. Bioinform., 2012

Metal Binding in Proteins: Machine Learning Complements X-Ray Absorption Spectroscopy.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

Improving activity recognition by segmental pattern mining.
Proceedings of the Tenth Annual IEEE International Conference on Pervasive Computing and Communications, 2012

Predicting virus mutations through relational learning.
Proceedings of the Workshop on Annotation, 2012

Using Machine Learning and Information Retrieval Techniques to Improve Software Maintainability.
Proceedings of the Trustworthy Eternal Systems via Evolving Software, Data and Knowledge, 2012

2011
MetalDetector v2.0: predicting the geometry of metal binding sites from protein sequence.
Nucleic Acids Res., 2011

Relational information gain.
Mach. Learn., 2011

Relational Feature Mining with Hierarchical Multitask kFOIL.
Fundam. Informaticae, 2011

Active Learning of Combinatorial Features for Interactive Optimization.
Proceedings of the Learning and Intelligent Optimization - 5th International Conference, 2011

2010
Brain-Computer Evolutionary Multiobjective Optimization: A Genetic Algorithm Adapting to the Decision Maker.
IEEE Trans. Evol. Comput., 2010

Fast learning of relational kernels.
Mach. Learn., 2010

Automatic prediction of catalytic residues by modeling residue structural neighborhood.
BMC Bioinform., 2010

An On/Off Lattice Approach to Protein Structure Prediction from Contact Maps.
Proceedings of the Pattern Recognition in Bioinformatics, 2010

Adapting to a Realistic Decision Maker: Experiments towards a Reactive Multi-objective Optimizer.
Proceedings of the Learning and Intelligent Optimization, 4th International Conference, 2010

From On-Going to Complete Activity Recognition Exploiting Related Activities.
Proceedings of the Human Behavior Understanding, First International Workshop, 2010

Predicting Structural and Functional Sites in Proteins by Searching for Maximum-weight Cliques.
Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010

2008
A simplified approach to disulfide connectivity prediction from protein sequences.
BMC Bioinform., 2008

MetalDetector: a web server for predicting metal-binding sites and disulfide bridges in proteins from sequence.
Bioinform., 2008

A semiparametric generative model for efficient structured-output supervised learning.
Ann. Math. Artif. Intell., 2008

Predicting the Geometry of Metal Binding Sites from Protein Sequence.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Learning with Kernels and Logical Representations.
Proceedings of the Probabilistic Inductive Logic Programming - Theory and Applications, 2008

Feature Discovery with Type Extension Trees.
Proceedings of the Inductive Logic Programming, 18th International Conference, 2008

On the Convergence of Protein Structure and Dynamics. Statistical Learning Studies of Pseudo Folding Pathways.
Proceedings of the Evolutionary Computation, 2008

2007
Predicting zinc binding at the proteome level.
BMC Bioinform., 2007

Automatic Classification of Provisions in Legislative Texts.
Artif. Intell. Law, 2007

2006
DISULFIND: a disulfide bonding state and cysteine connectivity prediction server.
Nucleic Acids Res., 2006

Kernels on Prolog Proof Trees: Statistical Learning in the ILP Setting.
J. Mach. Learn. Res., 2006

Improving Prediction of Zinc Binding Sites by Modeling the Linkage Between Residues Close in Sequence.
Proceedings of the Research in Computational Molecular Biology, 2006

Decomposition Kernels for Natural Language Processing.
Proceedings of the Workshop on Learning Structured Information in Natural Language Applications@EACL 2006, 2006

kFOIL: Learning Simple Relational Kernels.
Proceedings of the Proceedings, 2006

2005
Kernels on Prolog Ground Terms.
Proceedings of the IJCAI-05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 2005

Automatic semantics extraction in law documents.
Proceedings of the Tenth International Conference on Artificial Intelligence and Law, 2005

2004
Kernel methods, multiclass classification and applications to computational molecular biology.
PhD thesis, 2004

New results on error correcting output codes of kernel machines.
IEEE Trans. Neural Networks, 2004

2003
Predicting the Disulfide Bonding State of Cysteines with Combinations of Kernel Machines.
J. VLSI Signal Process., 2003

A Combination of Support Vector Machines and Bidirectional Recurrent Neural Networks for Protein Secondary Structure Prediction.
Proceedings of the AI*IA 2003: Advances in Artificial Intelligence, 2003

2002
A two-stage SVM architecture for predicting the disulfide bonding state of cysteines.
Proceedings of the 12th IEEE Workshop on Neural Networks for Signal Processing, 2002

From Margins to Probabilities in Multiclass Learning Problems.
Proceedings of the 15th European Conference on Artificial Intelligence, 2002

2001
Evaluation Methods for Focused Crawling.
Proceedings of the AI*IA 2001: Advances in Artificial Intelligence, 2001


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