A. Sperduti

Alessio Micheli, Alessandro Sperduti, Antonina Starita, 1998, 1998 IEEE International Joint Conference on Neural Networks Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36227).

Heuristics Miners for Streaming Event Data

Alessandro Sperduti, Wil M. P. van der Aalst, Wil M.P. van der Aalst, 2012, ArXiv.

Kernel Machines, Neural Networks, and Graphical Models

Alessandro Sperduti, Paolo Frasconi, Antonina Starita, 2006, Intelligenza Artificiale.

Classification of Structures by Recurrent Neural Networks

A. Sperduti, A. Starita, 1997 .

Are Professional Kitchens Ready for Dummies? A Comparative Usability Evaluation Between Expert and Non-expert Users

Alessandro Sperduti, Luciano Gamberini, Valeria Orso, 2021, HCI.

Guest Editors' Introduction: Special Section on Connectionist Models for Learning in Structured Domains

Alessandro Sperduti, Paolo Frasconi, Marco Gori, 2001, IEEE Trans. Knowl. Data Eng..

Complex Data: Learning Trustworthily, Automatically, and with Guarantees

Alessio Micheli, Franco Scarselli, Alessandro Sperduti, 2021, ESANN.

Compositional generative mapping of structured data

Davide Bacciu, Alessio Micheli, Alessandro Sperduti, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

A Bottom-up Hidden Tree Markov Model

A. Micheli, A. Sperduti, D. Bacciu, 2010 .

Extended Cascade-Correlat ion for Syntact ic and Structural Pat tern Recogni t ion

A. Sperduti, D. Majidi, 2005 .

Conditional Variational Capsule Network for Open Set Recognition pdf

Alessandro Sperduti, Lamberto Ballan, Guglielmo Camporese, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).

A QSAR study of A1adenosine receptor antagonists by a new neural network model

Alessio Micheli, Alessandro Sperduti, Antonina Starita, 2001 .

Computational Intelligence and Bioengineering

Alessio Micheli, Alessandro Sperduti, Francesco Masulli, 2009 .

A tutorial on neurocomputing of structures

Alessandro Sperduti, A. Sperduti, 2000 .

Deliverable 1 . 3 Modelling and processing services and tools

A. Sperduti, S. Kollet, C. Montzka, 2018 .

Preface: 9th International workshop on business process intelligence (BPI 2013)

Oscar Pastor, Mathias Weske, Hans Weigand, 2014, BPM 2014.

Generative Topographic Mapping Based Aggregation Function for GCNN

A. Sperduti, Paolo Frazzetto, Luca Pasa, 2022 .

Computational Intelligence and Bioengineering - Essays in Memory of Antonina Starita

Alessio Micheli, Alessandro Sperduti, Francesco Masulli, 2009, Computational Intelligence and Bioengineering.

A System for the Automatic Morphological Analysis of Mediaeval Manuscripts

Alessandro Sperduti, Antonina Starita, Francesco Masulli, 1996 .

Author Correction: Suppression of a SARS-CoV-2 outbreak in the Italian municipality of Vo’

E. Lavezzo, S. Toppo, A. Brazzale, 2021, Nature.

SOM-based aggregation for graph convolutional neural networks

A. Sperduti, Luca Pasa, Nicoló Navarin, 2020, Neural Computing and Applications.

Adaptive Contextual Processing of Structured Data by Recursive Neural Networks: A Survey of Computational Properties

Alessio Micheli, Alessandro Sperduti, Barbara Hammer, 2007, Perspectives of Neural-Symbolic Integration.

Special issue on neural networks and kernel methods for structured domains

Alessandro Sperduti, Barbara Hammer, Craig Saunders, 2005, Neural Networks.

Towards learning trustworthily, automatically, and with guarantees on graphs: An overview

M. Bianchini, F. Scarselli, A. Micheli, 2022, Neurocomputing.

Artificial Neural Network Models

Peter Tiño, Alessandro Sperduti, Lubica Benusková, 2015, Handbook of Computational Intelligence.

Neural Networks for Sequential Data: a Pre-training Approach based on Hidden Markov Models

Alessandro Sperduti, Luca Pasa, Alberto Testolin, 2015, Neurocomputing.

Multilayer Graph Node Kernels: Stacking While Maintaining Convexity

Alessandro Sperduti, Davide Anguita, Luca Oneto, 2018, Neural Processing Letters.

Learning Orthographic Structure With Sequential Generative Neural Networks

Alessandro Sperduti, Alberto Testolin, Marco Zorzi, 2016, Cogn. Sci..

Efficient Computation of Recursive Principal Component Analysis for Structured Input

Alessandro Sperduti, A. Sperduti, 2007, ECML.

Exact Solutions for Recursive Principal Components Analysis of Sequences and Trees

Alessandro Sperduti, A. Sperduti, 2006, ICANN.

Application of Cascade Correlation Networks for Structures to Chemistry

Alessio Micheli, Alessandro Sperduti, Antonina Starita, 2004, Applied Intelligence.

Special issue on integration of symbolic and connectionist systems

Franz J. Kurfess, Alessandro Sperduti, Paolo Frasconi, 2002, Cognitive Systems Research.

Learning Efficiently with Neural Networks: A Theoretical Comparison between Structured and Flat Representations

Alessandro Sperduti, Paolo Frasconi, Marco Gori, 2000, ECAI.

On the implementation of frontier-to-root tree automata in recursive neural networks

Alessandro Sperduti, Marco Gori, Andreas Küchler, 1999, IEEE Trans. Neural Networks.

Integration of Graphical Rules with Adaptive Learning of Structured Information

Alessandro Sperduti, Paolo Frasconi, Marco Gori, 1998, Hybrid Neural Systems.

Neural Networks for Processing Data Structures

Alessandro Sperduti, A. Sperduti, 1997, Summer School on Neural Networks.

On the Efficient Classification of Data Structures by Neural Networks

Alessandro Sperduti, Paolo Frasconi, Marco Gori, 1997, IJCAI.

An overview on supervised neural networks for structures

A. Sperduti, A. Sperduti, 1997, Proceedings of International Conference on Neural Networks (ICNN'97).

Supervised neural networks for the classification of structures

Alessandro Sperduti, Antonina Starita, A. Sperduti, 1997, IEEE Trans. Neural Networks.

Distributed representations for terms in hybrid reasoning systems

Alessandro Sperduti, Christoph Goller, Antonina Starita, 1997 .

A memory model based on LRAAM for associative access of structures

A. Sperduti, A. Starita, A. Sperduti, 1996, Proceedings of International Conference on Neural Networks (ICNN'96).

Stability properties of labeling recursive auto-associative memory

Alessandro Sperduti, A. Sperduti, 1995, IEEE Trans. Neural Networks.

Learning Distributed Representations for the Classification of Terms

Alessandro Sperduti, Christoph Goller, Antonina Starita, 1995, IJCAI.

Modular Labeling RAAM

Alessandro Sperduti, Antonina Starita, A. Sperduti, 1995, ICANNGA.

Dynamical Neural Networks Construction for Processing of Labeled Structures

A. Sperduti, A. Starita, A. Sperduti, 1995 .

Encoding pyramids by Labeling RAAM

A. Sperduti, A. Starita, Stefano Lonardi, 1994, Proceedings of IEEE Workshop on Neural Networks for Signal Processing.

On the access by content capabilities of the LRAAM

A. Sperduti, A. Starita, A. Sperduti, 1994, Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94).

Labelling Recursive Auto-associative Memory

Alessandro Sperduti, A. Sperduti, 1994, Connect. Sci..

Encoding Labeled Graphs by Labeling RAAM

Alessandro Sperduti, A. Sperduti, 1993, NIPS.

On Some Stability Properties of the LRAAM Model

Alessandro Sperduti, A. Sperduti, 1993 .

An Example of Neural Code: Neural Trees Implemented by LRAAMs

Alessandro Sperduti, Antonina Starita, A. Sperduti, 1993 .

A Lossy Counting Based Approach for Learning on Streams of Graphs on a Budget

Alessandro Sperduti, Giovanni Da San Martino, Nicolò Navarin, 2013, IJCAI.

On the Need for a Neural Abstract Machine

Alessandro Sperduti, Diego Sona, A. Sperduti, 2001, Sequence Learning.

Heterogeneous networks integration for disease-gene prioritization with node kernels

Alessandro Sperduti, Rolf Backofen, Dinh Van Tran, 2020, Bioinform..

Scuba: scalable kernel-based gene prioritization

Giorgio Valle, Alessandro Sperduti, Fabio Aiolli, 2018, BMC Bioinformatics.

DEEP: decomposition feature enhancement procedure for graphs

Alessandro Sperduti, Nicolò Navarin, Dinh Tran-Van, 2018, ESANN.

The Conjunctive Disjunctive Node Kernel

Alessandro Sperduti, Dinh Tran-Van, Fabrizio Costa, 2017, ESANN.

Solving and learning a tractable class of soft temporal constraints: Theoretical and experimental results

Alessandro Sperduti, Francesca Rossi, Lina Khatib, 2007, AI Commun..

Learning and Solving Soft Temporal Constraints: An Experimental Study

Alessandro Sperduti, Francesca Rossi, Lina Khatib, 2002, CP.

Learning preferences on temporal constraints: a preliminary report

Alessandro Sperduti, Francesca Rossi, Lina Khatib, 2001, Proceedings Eighth International Symposium on Temporal Representation and Reasoning. TIME 2001.

Suppression of a SARS-CoV-2 outbreak in the Italian municipality of Vo’

S. Bhatt, E. Lavezzo, S. Toppo, 2020, Nature.

Learning solution preferences in constraint problems

Alessandro Sperduti, Francesca Rossi, F. Rossi, 1998, J. Exp. Theor. Artif. Intell..

Universal Readout for Graph Convolutional Neural Networks

Alessandro Sperduti, Nicolò Navarin, Dinh Van Tran, 2019, 2019 International Joint Conference on Neural Networks (IJCNN).

Mining Structured Data

Alessandro Sperduti, Giovanni Da San Martino, A. Sperduti, 2010, IEEE Computational Intelligence Magazine.

Self-Organizing Maps for Structured Domains: Theory, Models, and Learning of Kernels

Markus Hagenbuchner, Alessandro Sperduti, Giovanni Da San Martino, 2009, Innovations in Neural Information Paradigms and Applications.

Efficient Kernel-based Learning for Trees

Alessandro Sperduti, Alessandro Moschitti, Giovanni Da San Martino, 2007, 2007 IEEE Symposium on Computational Intelligence and Data Mining.

Fast On-line Kernel Learning for Trees

Alessandro Sperduti, Alessandro Moschitti, Giovanni Da San Martino, 2006, Sixth International Conference on Data Mining (ICDM'06).

Unsupervised clustering of continuous trajectories of kinematic trees with SOM-SD

Alessandro Sperduti, Jochen J. Steil, Risto Kõiva, 2006, ESANN.

Recursive self-organizing network models

Alessio Micheli, Alessandro Sperduti, Barbara Hammer, 2004, Neural Networks.

A general framework for unsupervised processing of structured data

Alessio Micheli, Alessandro Sperduti, Barbara Hammer, 2004, Neurocomputing.

A preliminary empirical comparison of recursive neural networks and tree kernel methods on regression tasks for tree structured domains

A. Micheli, A. Sperduti, F. Portera, 2005, Neurocomputing.

An introduction to recursive neural networks and kernel methods for cheminformatics.

Alessio Micheli, Alessandro Sperduti, Antonina Starita, 2007, Current pharmaceutical design.

A preliminary experimental comparison of recursive neural networks and a tree kernel method for QSAR/QSPR regression tasks

Alessio Micheli, Alessandro Sperduti, Filippo Portera, 2004, ESANN.

QSAR/QSPR Studies by Kernel Machines, Recursive Neural Networks and Their Integration

Alessio Micheli, Alessandro Sperduti, Filippo Portera, 2003, WIRN.

Predicting Thermodynamic Properties from Molecular Structures by Recursive Neural Networks

Alessio Micheli, Alessandro Sperduti, Antonina Starita, 2004 .

Design of new biologically active molecules by recursive neural networks

Alessio Micheli, Alessandro Sperduti, Antonina Starita, 2001, IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222).

Analysis of the Internal Representations Developed by Neural Networks for Structures Applied to Quantitative Structure-Activity Relationship Studies of Benzodiazepines

Alessio Micheli, Alessandro Sperduti, Antonina Starita, 2001, J. Chem. Inf. Comput. Sci..

Extended Cascade-Correlation for Syntactic and Structural Pattern Recognition

Alessandro Sperduti, Antonina Starita, Darya Majidi, 1996, SSPR.

Process Mining Manifesto

Ricardo Seguel, Paola Mello, Donato Malerba, 2011, Business Process Management Workshops.

Boosting algorithms for automated text categorization

Alessandro Sperduti, Fabrizio Sebastiani, Nicola Valdambrini, 2001 .

Multiresolution Reservoir Graph Neural Network

A. Sperduti, Luca Pasa, Nicoló Navarin, 2021, IEEE Transactions on Neural Networks and Learning Systems.

Polynomial-based graph convolutional neural networks for graph classification

A. Sperduti, Luca Pasa, Nicoló Navarin, 2021, Machine-mediated learning.

VT-LINKER: Visual-Textual-Knowledge Entity Linker

Alessandro Sperduti, Lamberto Ballan, Luciano Serafini, 2020, ECAI.

ANASTASIA: ANdroid mAlware detection using STatic analySIs of Applications

Mauro Conti, Alessandro Sperduti, Danfeng Yao, 2016, 2016 8th IFIP International Conference on New Technologies, Mobility and Security (NTMS).

Backpropagation-free Graph Neural Networks

A. Sperduti, W. Erb, Luca Pasa, 2022, 2022 IEEE International Conference on Data Mining (ICDM).

Compact graph neural network models for node classification

A. Sperduti, Luca Pasa, Nicoló Navarin, 2022, SAC.

A self-organizing map for adaptive processing of structured data

Ah Chung Tsoi, Markus Hagenbuchner, Alessandro Sperduti, 2003, IEEE Trans. Neural Networks.

Universal Approximation Capability of Cascade Correlation for Structures

Alessio Micheli, Alessandro Sperduti, Barbara Hammer, 2005, Neural Computation.

Route kernels for trees

Alessandro Sperduti, Giovanni Da San Martino, Fabio Aiolli, 2009, ICML '09.

Pre-training of Recurrent Neural Networks via Linear Autoencoders

Alessandro Sperduti, Luca Pasa, A. Sperduti, 2014, NIPS.

Data-aware remaining time prediction of business process instances

Alessandro Sperduti, Massimiliano de Leoni, Mirko Polato, 2014, 2014 International Joint Conference on Neural Networks (IJCNN).

Multi-task learning for the prediction of wind power ramp events with deep neural networks

Pedro Antonio Gutiérrez, M Dorado-Moreno, N Navarin, 2020, Neural Networks.

Hand control by a neural network using tactile and positional information

A. Sperduti, A. Starita, A. Sperduti, 1991, Fifth International Conference on Advanced Robotics 'Robots in Unstructured Environments.

Multi-prototype Support Vector Machine

Alessandro Sperduti, Fabio Aiolli, A. Sperduti, 2003, IJCAI.

VTKEL: a resource for visual-textual-knowledge entity linking

Alessandro Sperduti, Lamberto Ballan, Luciano Serafini, 2020, SAC.

Control-flow discovery from event streams

Wil M.P. van der Aalst, A. Sperduti, Andrea Burattin, 2014, 2014 IEEE Congress on Evolutionary Computation (CEC).

Linear dynamical based models for sequential domains

Peter Tiño, Alessandro Sperduti, Luca Pasa, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

Acquiring Both Constraint and Solution Preferences in Interactive Constraint Systems

Alessandro Sperduti, Francesca Rossi, F. Rossi, 2004, Constraints.

Short-Term Memory Optimization in Recurrent Neural Networks by Autoencoder-based Initialization pdf

Alessandro Sperduti, Antonio Carta, Davide Bacciu, 2020, ArXiv.

On the Computational Power of Recurrent Neural Networks for Structures

Alessandro Sperduti, A. Sperduti, 1997, Neural Networks.

Probabilistic Modeling in Machine Learning

Paulo J. G. Lisboa, Thomas Villmann, Davide Bacciu, 2015, Handbook of Computational Intelligence.

Heuristics Miners for Streaming Event Data pdf

Alessandro Sperduti, Wil M. P. van der Aalst, Wil M.P. van der Aalst, 2012, ArXiv.

Automatic determination of parameters' values for Heuristics Miner++

Alessandro Sperduti, Andrea Burattin, A. Sperduti, 2010, IEEE Congress on Evolutionary Computation.

Heuristics Miner for Time Intervals

Alessandro Sperduti, Andrea Burattin, A. Sperduti, 2010, ESANN.

Conformance checking based on multi-perspective declarative process models

Alessandro Sperduti, Fabrizio Maria Maggi, Andrea Burattin, 2015, Expert Syst. Appl..

Online Discovery of Declarative Process Models from Event Streams

Alessandro Sperduti, Fabrizio Maria Maggi, Marta Cimitile, 2015, IEEE Transactions on Services Computing.

Discovering high-level BPMN process models from event data

Alessandro Sperduti, Wil M. P. van der Aalst, Massimiliano de Leoni, 2018, Bus. Process. Manag. J..

Challenges in Deep Learning

Alessandro Sperduti, Plamen Angelov, A. Sperduti, 2016, ESANN.

The loading problem for recursive neural networks

Alessandro Sperduti, Marco Gori, M. Gori, 2005, Neural Networks.

A Hybrid System for Systematic Generalization in Simple Arithmetic Problems

Alberto Testolin, A. Sperduti, Flavio Petruzzellis, 2023, NeSy.

Encoding-based memory for recurrent neural networks

Davide Bacciu, Alessandro Sperduti, Antonio Carta, 2021, Neurocomputing.

Pre-training Graph Neural Networks with Kernels pdf

Alessandro Sperduti, Nicolò Navarin, Dinh Van Tran, 2018, ArXiv.

On Filter Size in Graph Convolutional Networks

Alessandro Sperduti, Nicolò Navarin, Dinh Van Tran, 2018, 2018 IEEE Symposium Series on Computational Intelligence (SSCI).

Graph Kernels Exploiting Weisfeiler-Lehman Graph Isomorphism Test Extensions pdf

Alessandro Sperduti, Giovanni Da San Martino, Nicolò Navarin, 2014, ICONIP.

Learning Preferences for Multiclass Problems

Alessandro Sperduti, Fabio Aiolli, A. Sperduti, 2004, NIPS.

Conditional Constrained Graph Variational Autoencoders for Molecule Design

Alessandro Sperduti, Nicolo Navarin, Davide Rigoni, 2020, 2020 IEEE Symposium Series on Computational Intelligence (SSCI).

Theoretical and Experimental Analysis of a Two-Stage System for Classification

Alessandro Sperduti, Francesco Masulli, Nicola Giusti, 2002, IEEE Trans. Pattern Anal. Mach. Intell..

Business models enhancement through discovery of roles

Alessandro Sperduti, Andrea Burattin, Marco Veluscek, 2013, 2013 IEEE Symposium on Computational Intelligence and Data Mining (CIDM).

Embeddings and Representation Learning for Structured Data pdf

Claudio Gallicchio, Alessio Micheli, Alessandro Sperduti, 2019, ESANN.

Approximated Neighbours MinHash Graph Node Kernel

Alessandro Sperduti, Nicolò Navarin, A. Sperduti, 2017, ESANN.

A General Framework for Self-Organizing Structure Processing Neural Networks

Alessio Micheli, Alessandro Sperduti, Barbara Hammer, 2003 .

A general framework for unsupervisedprocessing of structuredd ata

Alessio Micheli, Alessandro Sperduti, Barbara Hammer, 2004 .

Learning With Kernels: A Local Rademacher Complexity-Based Analysis With Application to Graph Kernels

Alessandro Sperduti, Davide Anguita, Luca Oneto, 2018, IEEE Transactions on Neural Networks and Learning Systems.

Generative Kernels for Tree-Structured Data

Davide Bacciu, Alessio Micheli, Alessandro Sperduti, 2018, IEEE Transactions on Neural Networks and Learning Systems.

Measuring the expressivity of graph kernels through Statistical Learning Theory

Alessandro Sperduti, Davide Anguita, Luca Oneto, 2017, Neurocomputing.

Extending local features with contextual information in graph kernels

Alessandro Sperduti, Nicolò Navarin, Riccardo Tesselli, 2015, ICONIP.

Learning Kernel-Based Embeddings in Graph Neural Networks

Alessandro Sperduti, Nicolò Navarin, Dinh Van Tran, 2020, ECAI.

PLG: A Framework for the Generation of Business Process Models and Their Execution Logs

Alessandro Sperduti, Andrea Burattin, A. Sperduti, 2010, Business Process Management Workshops.

Encoding-based Memory Modules for Recurrent Neural Networks pdf

Davide Bacciu, Alessandro Sperduti, Antonio Carta, 2020, ArXiv.

Linear Memory Networks pdf

Davide Bacciu, Alessandro Sperduti, Antonio Carta, 2018, ICANN.

Learning Sequential Data with the Help of Linear Systems

Alessandro Sperduti, Luca Pasa, A. Sperduti, 2016, ANNPR.

Equivalence Results between Feedforward and Recurrent Neural Networks for Sequences

Alessandro Sperduti, A. Sperduti, 2015, IJCAI.

A HMM-based pre-training approach for sequential data

Alessandro Sperduti, Luca Pasa, Alberto Testolin, 2014, ESANN.

A Tree-Based Kernel for Graphs

Alessandro Sperduti, Giovanni Da San Martino, Nicolò Navarin, 2012, SDM.

Multiple Graph-Kernel Learning

Alessandro Sperduti, Fabio Aiolli, Nicolò Navarin, 2015, 2015 IEEE Symposium Series on Computational Intelligence.

An improved boosting algorithm and its application to text categorization

Alessandro Sperduti, Fabrizio Sebastiani, Nicola Valdambrini, 2000, CIKM '00.

Time and activity sequence prediction of business process instances

A. Sperduti, M. Leoni, Mirko Polato, 2018, Computing.

Time and activity sequence prediction of business process instances

Alessandro Sperduti, Massimiliano de Leoni, Mirko Polato, 2016, Computing.

Measuring the Expressivity of Graph Kernels through the Rademacher Complexity

Alessandro Sperduti, Davide Anguita, Luca Oneto, 2016, ESANN.

A Kernel Method for the Optimization of the Margin Distribution

Alessandro Sperduti, Giovanni Da San Martino, Fabio Aiolli, 2008, ICANN.

Jointly Linking Visual and Textual Entity Mentions with Background Knowledge

Alessandro Sperduti, Lamberto Ballan, Marco Rospocher, 2020, NLDB.

Weakly-Supervised Visual-Textual Grounding with Semantic Prior Refinement

Lamberto Ballan, A. Sperduti, L. Serafini, 2023, arXiv.org.

Topology preserving maps as aggregations for Graph Convolutional Neural Networks

A. Sperduti, Paolo Frazzetto, Luca Pasa, 2023, SAC.

SOM-based aggregation for graph convolutional neural networks

Alessandro Sperduti, Luca Pasa, Nicolò Navarin, 2020, Neural Comput. Appl..

LSTM networks for data-aware remaining time prediction of business process instances

Alessandro Sperduti, Mirko Polato, Nicolò Navarin, 2017, 2017 IEEE Symposium Series on Computational Intelligence (SSCI).

A better loss for visual-textual grounding

A. Sperduti, L. Serafini, Davide Rigoni, 2021, SAC.

Predicting Physical-Chemical Properties of Compounds from Molecular Structures by Recursive Neural Networks

Alessio Micheli, Alessandro Sperduti, Antonina Starita, 2006, J. Chem. Inf. Model..

A Preference Optimization Based Unifying Framework for Supervised Learning Problems

Alessandro Sperduti, Fabio Aiolli, A. Sperduti, 2010, Preference Learning.

An Efficient Topological Distance-Based Tree Kernel

Alessandro Sperduti, Giovanni Da San Martino, Fabio Aiolli, 2015, IEEE Transactions on Neural Networks and Learning Systems.

Multiclass Classification with Multi-Prototype Support Vector Machines

Alessandro Sperduti, Fabio Aiolli, A. Sperduti, 2005, J. Mach. Learn. Res..

A Business Process Metric Based on the Alpha Algorithm Relations

Alessandro Sperduti, Fabio Aiolli, Andrea Burattin, 2011, Business Process Management Workshops.

Joint Neighborhood Subgraphs Link Prediction

Alessandro Sperduti, Dinh Tran-Van, Fabrizio Costa, 2017, ICONIP.

RGCVAE: Relational Graph Conditioned Variational Autoencoder for Molecule Design

A. Sperduti, Nicoló Navarin, Davide Rigoni, 2023, ArXiv.

Hidden Recursive Models

Alessandro Sperduti, Paolo Frasconi, Marco Gori, 1998 .

Contextual Processing of Graphs using Self-Organizing Maps

Ah Chung Tsoi, Markus Hagenbuchner, Alessandro Sperduti, 2005, ESANN.

Efficient Online Learning for Mapping Kernels on Linguistic Structures

Alessandro Sperduti, Alessandro Moschitti, Giovanni Da San Martino, 2019, AAAI.

An empirical study on budget-aware online kernel algorithms for streams of graphs

Alessandro Sperduti, Giovanni Da San Martino, Nicolò Navarin, 2015, Neurocomputing.

A Generalized Quadratic Loss for Support Vector Machines

Alessandro Sperduti, Filippo Portera, A. Sperduti, 2004, ECAI.

Support Vector Regression with a Generalized Quadratic Loss

Alessandro Sperduti, Filippo Portera, A. Sperduti, 2004, WIRN.

Author Correction: Suppression of a SARS-CoV-2 outbreak in the Italian municipality of Vo’

A. Crisanti, S. Bhatt, E. Lavezzo, 2021, Nature.

Multilayer Graph Node Kernels: Stacking While Maintaining Convexity

A. Sperduti, L. Oneto, D. Anguita, 2018, Neural Processing Letters.

Ordered Decompositional DAG kernels enhancements pdf

Alessandro Sperduti, Giovanni Da San Martino, Nicolò Navarin, 2015, Neurocomputing.

Logo Recognition by Recursive Neural Networks

P. Frasconi, M. Gori, G. Soda, 1997, GREC.

A Generative Multiset Kernel for Structured Data

Davide Bacciu, Alessio Micheli, Alessandro Sperduti, 2012, ICANN.

The loading problem for recursive neural networks

M. Gori, A. Sperduti, 2005, Neural Networks.

Link Enrichment for Diffusion-Based Graph Node Kernels

A. Sperduti, Fabrizio Costa, Dinh Tran-Van, 2017, ICANN.

Graph self-organizing maps for cyclic and unbounded graphs

A. Tsoi, M. Hagenbuchner, A. Sperduti, 2009, Neurocomputing.

Learning Nonsparse Kernels by Self-Organizing Maps for Structured Data

Markus Hagenbuchner, Alessandro Sperduti, Giovanni Da San Martino, 2009, IEEE Transactions on Neural Networks.

Efficient Clustering of Structured Documents Using Graph Self-Organizing Maps

Ah Chung Tsoi, Markus Hagenbuchner, Alessandro Sperduti, 2008, INEX.

Formal Determination of Context in Contextual Recursive Cascade Correlation Networks

Alessio Micheli, Alessandro Sperduti, Diego Sona, 2003, ICANN.

Self-Organizing Maps for cyclic and unbounded graphs

Ah Chung Tsoi, Markus Hagenbuchner, Alessandro Sperduti, 2008, ESANN.

A Supervised Self-Organizing Map for Structured Data

Ah Chung Tsoi, Markus Hagenbuchner, Alessandro Sperduti, 2001, WSOM.

Business Process Management Workshops

Niels Lohmann, Petia Wohed, Minseok Song, 2013, Lecture Notes in Business Information Processing.

Tree-Based Kernel for Graphs With Continuous Attributes

Alessandro Sperduti, Nicolò Navarin, Giovanni Da San Martino, 2015, IEEE Transactions on Neural Networks and Learning Systems.

Biased Edge Dropout in NIFTY for Fair Graph Representation Learning

A. Sperduti, L. Oneto, Luca Pasa, 2022, ESANN.

Deep graph node kernels: A convex approach

Alessandro Sperduti, Davide Anguita, Luca Oneto, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

A Neural Rewriting System to Solve Algorithmic Problems

Alberto Testolin, A. Sperduti, Flavio Petruzzellis, 2024, ArXiv.

Benchmarking GPT-4 on Algorithmic Problems: A Systematic Evaluation of Prompting Strategies

Alberto Testolin, A. Sperduti, Flavio Petruzzellis, 2024, 2402.17396.

A novel criterion for overlapping communities detection and clustering improvement

Alessandro Sperduti, Alessandro Berti, Andrea Burattin, 2014, 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM).

On Backpropagation-Free Graph Convolutions

A. Sperduti, Luca Pasa, Nicoló Navarin, 2022 .

The conjunctive disjunctive graph node kernel for disease gene prioritization

Alessandro Sperduti, Fabrizio Costa, Dinh Tran-Van, 2018, Neurocomputing.

Empowering Simple Graph Convolutional Networks

A. Sperduti, W. Erb, Luca Pasa, 2023, IEEE Transactions on Neural Networks and Learning Systems.

Over-Parameterized Neural Models based on Graph Random Features for fast and accurate graph classification

A. Sperduti, L. Oneto, Luca Pasa, 2023 .

TumFlow: An AI Model for Predicting New Anticancer Molecules

A. Sperduti, Nicoletta Bianchi, Davide Rigoni, 2024, bioRxiv.

A Systematic Assessment of Deep Learning Models for Molecule Generation

Alessandro Sperduti, Nicolo Navarin, Davide Rigoni, 2020, ESANN.