Alessandro Sperduti

Orcid: 0000-0002-8686-850X

Affiliations:
  • University of Padua, Italy


According to our database1, Alessandro Sperduti authored at least 221 papers between 1993 and 2024.

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

Timeline

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Bibliography

2024
Empowering Simple Graph Convolutional Networks.
IEEE Trans. Neural Networks Learn. Syst., April, 2024

A unified framework for backpropagation-free soft and hard gated graph neural networks.
Knowl. Inf. Syst., April, 2024

A Neural Rewriting System to Solve Algorithmic Problems.
CoRR, 2024

Benchmarking GPT-4 on Algorithmic Problems: A Systematic Evaluation of Prompting Strategies.
CoRR, 2024

2023
RGCVAE: Relational Graph Conditioned Variational Autoencoder for Molecule Design.
CoRR, 2023

Topology preserving maps as aggregations for Graph Convolutional Neural Networks.
Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing, 2023

A Hybrid System for Systematic Generalization in Simple Arithmetic Problems.
Proceedings of the 17th International Workshop on Neural-Symbolic Learning and Reasoning, 2023

Enhancing Human Resources through Data Science: a Case in Recruiting.
Proceedings of the 2nd Italian Conference on Big Data and Data Science (ITADATA 2023), 2023

Weakly-Supervised Visual-Textual Grounding with Semantic Prior Refinement.
Proceedings of the 34th British Machine Vision Conference 2023, 2023

2022
Multiresolution Reservoir Graph Neural Network.
IEEE Trans. Neural Networks Learn. Syst., 2022

SOM-based aggregation for graph convolutional neural networks.
Neural Comput. Appl., 2022

Polynomial-based graph convolutional neural networks for graph classification.
Mach. Learn., 2022

Towards learning trustworthily, automatically, and with guarantees on graphs: An overview.
Neurocomputing, 2022

Aligning and linking entity mentions in image, text, and knowledge base.
Data Knowl. Eng., 2022

Conference Report on 2022 IEEE World Congress on Computational Intelligence (IEEE WCCI 2022).
IEEE Comput. Intell. Mag., 2022

A better loss for visual-textual grounding.
Proceedings of the SAC '22: The 37th ACM/SIGAPP Symposium on Applied Computing, Virtual Event, April 25, 2022

Compact graph neural network models for node classification.
Proceedings of the SAC '22: The 37th ACM/SIGAPP Symposium on Applied Computing, Virtual Event, April 25, 2022

Backpropagation-free Graph Neural Networks.
Proceedings of the IEEE International Conference on Data Mining, 2022

Biased Edge Dropout in NIFTY for Fair Graph Representation Learning.
Proceedings of the 30th European Symposium on Artificial Neural Networks, 2022

2021
Encoding-based memory for recurrent neural networks.
Neurocomputing, 2021

Simple Graph Convolutional Networks.
CoRR, 2021

Simple Multi-resolution Gated GNN.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2021

Conditional Variational Capsule Network for Open Set Recognition.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Are Professional Kitchens Ready for Dummies? A Comparative Usability Evaluation Between Expert and Non-expert Users.
Proceedings of the Human-Computer Interaction. Design and User Experience Case Studies, 2021

Tangent Graph Convolutional Network.
Proceedings of the 29th European Symposium on Artificial Neural Networks, 2021

Complex Data: Learning Trustworthily, Automatically, and with Guarantees.
Proceedings of the 29th European Symposium on Artificial Neural Networks, 2021

2020
Multi-task learning for the prediction of wind power ramp events with deep neural networks.
Neural Networks, 2020

Advances in artificial neural networks, machine learning and computational intelligence.
Neurocomputing, 2020

A framework for the definition of complex structured feature spaces.
Neurocomputing, 2020

Short-Term Memory Optimization in Recurrent Neural Networks by Autoencoder-based Initialization.
CoRR, 2020

Encoding-based Memory Modules for Recurrent Neural Networks.
CoRR, 2020

Heterogeneous networks integration for disease-gene prioritization with node kernels.
Bioinform., 2020

Conditional Constrained Graph Variational Autoencoders for Molecule Design.
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

On Visual-Textual-Knowledge Entity Linking.
Proceedings of the IEEE 14th International Conference on Semantic Computing, 2020

VTKEL: a resource for visual-textual-knowledge entity linking.
Proceedings of the SAC '20: The 35th ACM/SIGAPP Symposium on Applied Computing, online event, [Brno, Czech Republic], March 30, 2020

Incremental Training of a Recurrent Neural Network Exploiting a Multi-scale Dynamic Memory.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

Jointly Linking Visual and Textual Entity Mentions with Background Knowledge.
Proceedings of the Natural Language Processing and Information Systems, 2020

Towards Online Discovery of Data-Aware Declarative Process Models from Event Streams.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

A Systematic Assessment of Deep Learning Models for Molecule Generation.
Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020

Deep Recurrent Graph Neural Networks.
Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020

Linear Graph Convolutional Networks.
Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020

Learning Kernel-Based Embeddings in Graph Neural Networks.
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

VT-LINKER: Visual-Textual-Knowledge Entity Linker.
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

2019
Discovering high-level BPMN process models from event data.
Bus. Process. Manag. J., 2019

Integrating kitchen appliances to improve food quality and sustainability: the SIAF project.
Proceedings of the 12th ACM International Conference on PErvasive Technologies Related to Assistive Environments, 2019

Introduction.
Proceedings of the Recent Trends in Learning From Data, 2019

Universal Readout for Graph Convolutional Neural Networks.
Proceedings of the International Joint Conference on Neural Networks, 2019

Linear Memory Networks.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019: Theoretical Neural Computation, 2019

Embeddings and Representation Learning for Structured Data.
Proceedings of the 27th European Symposium on Artificial Neural Networks, 2019

On the definition of complex structured feature spaces.
Proceedings of the 27th European Symposium on Artificial Neural Networks, 2019

Efficient Online Learning for Mapping Kernels on Linguistic Structures.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Learning With Kernels: A Local Rademacher Complexity-Based Analysis With Application to Graph Kernels.
IEEE Trans. Neural Networks Learn. Syst., 2018

Tree-Based Kernel for Graphs With Continuous Attributes.
IEEE Trans. Neural Networks Learn. Syst., 2018

Generative Kernels for Tree-Structured Data.
IEEE Trans. Neural Networks Learn. Syst., 2018

Multilayer Graph Node Kernels: Stacking While Maintaining Convexity.
Neural Process. Lett., 2018

The conjunctive disjunctive graph node kernel for disease gene prioritization.
Neurocomputing, 2018

Pre-training Graph Neural Networks with Kernels.
CoRR, 2018

Time and activity sequence prediction of business process instances.
Computing, 2018

Scuba: scalable kernel-based gene prioritization.
BMC Bioinform., 2018

On Filter Size in Graph Convolutional Networks.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2018

Extreme Graph Kernels for Online Learning on a Memory Budget.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

DEEP: decomposition feature enhancement procedure for graphs.
Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018

2017
Measuring the expressivity of graph kernels through Statistical Learning Theory.
Neurocomputing, 2017

LSTM networks for data-aware remaining time prediction of business process instances.
Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

Linear dynamical based models for sequential domains.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Deep graph node kernels: A convex approach.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

A kernel-based ensemble classifier for evolving stream of trees with double concept drifting reaction.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Joint Neighborhood Subgraphs Link Prediction.
Proceedings of the Neural Information Processing - 24th International Conference, 2017

Link Enrichment for Diffusion-Based Graph Node Kernels.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2017, 2017

The Conjunctive Disjunctive Node Kernel.
Proceedings of the 25th European Symposium on Artificial Neural Networks, 2017

Approximated Neighbours MinHash Graph Node Kernel.
Proceedings of the 25th European Symposium on Artificial Neural Networks, 2017

2016
An empirical study on budget-aware online kernel algorithms for streams of graphs.
Neurocomputing, 2016

Ordered Decompositional DAG kernels enhancements.
Neurocomputing, 2016

Conformance checking based on multi-perspective declarative process models.
Expert Syst. Appl., 2016

Learning Orthographic Structure With Sequential Generative Neural Networks.
Cogn. Sci., 2016

ANASTASIA: ANdroid mAlware detection using STatic analySIs of Applications.
Proceedings of the 8th IFIP International Conference on New Technologies, 2016

Hyper-Parameter Tuning for Graph Kernels via Multiple Kernel Learning.
Proceedings of the Neural Information Processing - 23rd International Conference, 2016

Measuring the Expressivity of Graph Kernels through the Rademacher Complexity.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

Challenges in Deep Learning.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

Learning Sequential Data with the Help of Linear Systems.
Proceedings of the Artificial Neural Networks in Pattern Recognition, 2016

2015
Artificial Neural Network Models.
Proceedings of the Springer Handbook of Computational Intelligence, 2015

Probabilistic Modeling in Machine Learning.
Proceedings of the Springer Handbook of Computational Intelligence, 2015

Online Discovery of Declarative Process Models from Event Streams.
IEEE Trans. Serv. Comput., 2015

An Efficient Topological Distance-Based Tree Kernel.
IEEE Trans. Neural Networks Learn. Syst., 2015

Neural Networks for Sequential Data: a Pre-training Approach based on Hidden Markov Models.
Neurocomputing, 2015

Multiple Graph-Kernel Learning.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2015

Equivalence Results between Feedforward and Recurrent Neural Networks for Sequences.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Extending Local Features with Contextual Information in Graph Kernels.
Proceedings of the Neural Information Processing - 22nd International Conference, 2015

Exploiting the ODD framework to define a novel effective graph kernel.
Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

2014
Pre-training of Recurrent Neural Networks via Linear Autoencoders.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Data-aware remaining time prediction of business process instances.
Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

Integrating bi-directional contexts in a generative kernel for trees.
Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

Graph Kernels Exploiting Weisfeiler-Lehman Graph Isomorphism Test Extensions.
Proceedings of the Neural Information Processing - 21st International Conference, 2014

Modeling Bi-directional Tree Contexts by Generative Transductions.
Proceedings of the Neural Information Processing - 21st International Conference, 2014

A HMM-based pre-training approach for sequential data.
Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

A novel criterion for overlapping communities detection and clustering improvement.
Proceedings of the 2014 IEEE Symposium on Computational Intelligence and Data Mining, 2014

Control-flow discovery from event streams.
Proceedings of the IEEE Congress on Evolutionary Computation, 2014

2013
Compositional Generative Mapping for Tree-Structured Data - Part II: Topographic Projection Model.
IEEE Trans. Neural Networks Learn. Syst., 2013

An input-output hidden Markov model for tree transductions.
Neurocomputing, 2013

Online Process Discovery to Detect Concept Drifts in LTL-Based Declarative Process Models.
Proceedings of the On the Move to Meaningful Internet Systems: OTM 2013 Conferences, 2013

A Lossy Counting Based Approach for Learning on Streams of Graphs on a Budget.
Proceedings of the IJCAI 2013, 2013

Business models enhancement through discovery of roles.
Proceedings of the IEEE Symposium on Computational Intelligence and Data Mining, 2013

2012
Compositional Generative Mapping for Tree-Structured Data - Part I: Bottom-Up Probabilistic Modeling of Trees.
IEEE Trans. Neural Networks Learn. Syst., 2012

Heuristics Miners for Streaming Event Data
CoRR, 2012

A Tree-Based Kernel for Graphs.
Proceedings of the Twelfth SIAM International Conference on Data Mining, 2012

A memory efficient graph kernel.
Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

A Generative Multiset Kernel for Structured Data.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2012, 2012

Assessment of sequential Boltmann machines on a lexical processing task.
Proceedings of the 20th European Symposium on Artificial Neural Networks, 2012

Input-Output Hidden Markov Models for trees.
Proceedings of the 20th European Symposium on Artificial Neural Networks, 2012

Techniques for a Posteriori Analysis of Declarative Processes.
Proceedings of the 16th IEEE International Enterprise Distributed Object Computing Conference, 2012

2011
Learning in the context of very high dimensional data (Dagstuhl Seminar 11341).
Dagstuhl Reports, 2011

Reasoning about service oriented recursion.
Proceedings of the 2011 IEEE International Conference on Service-Oriented Computing and Applications, 2011

Adaptive tree kernel by multinomial generative topographic mapping.
Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

Kernel-Based Selective Ensemble Learning for Streams of Trees.
Proceedings of the IJCAI 2011, 2011

Extending Tree Kernels with Topological Information.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2011, 2011

Sparsity Issues in Self-Organizing-Maps for Structures.
Proceedings of the 19th European Symposium on Artificial Neural Networks, 2011

A Business Process Metric Based on the Alpha Algorithm Relations.
Proceedings of the Business Process Management Workshops, 2011


2010
Mining Structured Data.
IEEE Comput. Intell. Mag., 2010

Compositional generative mapping of structured data.
Proceedings of the International Joint Conference on Neural Networks, 2010

Bottom-Up Generative Modeling of Tree-Structured Data.
Proceedings of the Neural Information Processing. Theory and Algorithms, 2010

A New Tree Kernel Based on SOM-SD.
Proceedings of the Artificial Neural Networks, 2010

Heuristics Miner for Time Intervals.
Proceedings of the 18th European Symposium on Artificial Neural Networks, 2010

Automatic determination of parameters' values for Heuristics Miner++.
Proceedings of the IEEE Congress on Evolutionary Computation, 2010

PLG: A Framework for the Generation of Business Process Models and Their Execution Logs.
Proceedings of the Business Process Management Workshops, 2010

A Preference Optimization Based Unifying Framework for Supervised Learning Problems.
Proceedings of the Preference Learning., 2010

2009
Self-Organizing Maps for Structured Domains: Theory, Models, and Learning of Kernels.
Proceedings of the Innovations in Neural Information Paradigms and Applications, 2009

Learning Nonsparse Kernels by Self-Organizing Maps for Structured Data.
IEEE Trans. Neural Networks, 2009

Graph self-organizing maps for cyclic and unbounded graphs.
Neurocomputing, 2009

Preferential Text Classification: Learning Algorithms and Evaluation Measures.
ERCIM News, 2009

Route kernels for trees.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

PCA-Based Representations of Graphs for Prediction in QSAR Studies.
Proceedings of the Artificial Neural Networks, 2009

Projection of undirected and non-positional graphs using Self Organizing Maps.
Proceedings of the 17th European Symposium on Artificial Neural Networks, 2009

Supervised learning as preference optimization.
Proceedings of the 17th European Symposium on Artificial Neural Networks, 2009

Application of the preference learning model to a human resources selection task.
Proceedings of the IEEE Symposium on Computational Intelligence and Data Mining, 2009

2008
Self Organizing Maps for the Clustering of Large Sets of Labeled Graphs.
Proceedings of the Advances in Focused Retrieval, 2008

A Kernel Method for the Optimization of the Margin Distribution.
Proceedings of the Artificial Neural Networks, 2008

Self-Organizing Maps for cyclic and unbounded graphs.
Proceedings of the 16th European Symposium on Artificial Neural Networks, 2008

2007
Adaptive Contextual Processing of Structured Data by Recursive Neural Networks: A Survey of Computational Properties.
Proceedings of the Perspectives of Neural-Symbolic Integration, 2007

Solving and learning a tractable class of soft temporal constraints: Theoretical and experimental results.
AI Commun., 2007

Efficient Clustering of Structured Documents Using Graph Self-Organizing Maps.
Proceedings of the Focused Access to XML Documents, 2007

Preference Learning for Category-Ranking based Interactive Text Categorization.
Proceedings of the International Joint Conference on Neural Networks, 2007

Recursive Principal Component Analysis of Graphs.
Proceedings of the Artificial Neural Networks, 2007

"Kernelized" Self-Organizing Maps for Structured Data.
Proceedings of the 15th European Symposium on Artificial Neural Networks, 2007

Efficient Computation of Recursive Principal Component Analysis for Structured Input.
Proceedings of the Machine Learning: ECML 2007, 2007

A general framework for unsupervised preocessing of structured data.
Proceedings of the Probabilistic, Logical and Relational Learning - A Further Synthesis, 15.04., 2007

Efficient Kernel-based Learning for Trees.
Proceedings of the IEEE Symposium on Computational Intelligence and Data Mining, 2007

2006
Predicting Physical-Chemical Properties of Compounds from Molecular Structures by Recursive Neural Networks.
J. Chem. Inf. Model., 2006

Kernel Machines, Neural Networks, and Graphical Models.
Intelligenza Artificiale, 2006

XML Document Mining Using Contextual Self-organizing Maps for Structures.
Proceedings of the Comparative Evaluation of XML Information Retrieval Systems, 2006

A Self-Organising Map Approach for Clustering of XML Documents.
Proceedings of the International Joint Conference on Neural Networks, 2006

Fast On-line Kernel Learning for Trees.
Proceedings of the 6th IEEE International Conference on Data Mining (ICDM 2006), 2006

Exact Solutions for Recursive Principal Components Analysis of Sequences and Trees.
Proceedings of the Artificial Neural Networks, 2006

Unsupervised clustering of continuous trajectories of kinematic trees with SOM-SD.
Proceedings of the 14th European Symposium on Artificial Neural Networks, 2006

Self-organising Map Techniques for Graph Data Applications to Clustering of XML Documents.
Proceedings of the Advanced Data Mining and Applications, Second International Conference, 2006

2005
Special issue on neural networks and kernel methods for structured domains.
Neural Networks, 2005

The loading problem for recursive neural networks.
Neural Networks, 2005

Universal Approximation Capability of Cascade Correlation for Structures.
Neural Comput., 2005

Multiclass Classification with Multi-Prototype Support Vector Machines.
J. Mach. Learn. Res., 2005

A preliminary empirical comparison of recursive neural networks and tree kernel methods on regression tasks for tree structured domains.
Neurocomputing, 2005

Clustering XML Documents Using Self-organizing Maps for Structures.
Proceedings of the Advances in XML Information Retrieval and Evaluation, 2005

Contextual Processing of Graphs using Self-Organizing Maps.
Proceedings of the 13th European Symposium on Artificial Neural Networks, 2005

2004
Contextual processing of structured data by recursive cascade correlation.
IEEE Trans. Neural Networks, 2004

Recursive self-organizing network models.
Neural Networks, 2004

A general framework for unsupervised processing of structured data.
Neurocomputing, 2004

Acquiring Both Constraint and Solution Preferences in Interactive Constraint Systems.
Constraints An Int. J., 2004

Support Vector Regression with a Generalized Quadratic Loss.
Proceedings of the Biological and Artificial Intelligence Environments, 2004

Learning Preferences for Multiclass Problems.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

A preliminary experimental comparison of recursive neural networks and a tree kernel method for QSAR/QSPR regression tasks.
Proceedings of the 12th European Symposium on Artificial Neural Networks, 2004

A Generalized Quadratic Loss for Support Vector Machines.
Proceedings of the 16th Eureopean Conference on Artificial Intelligence, 2004

2003
A self-organizing map for adaptive processing of structured data.
IEEE Trans. Neural Networks, 2003

QSAR/QSPR Studies by Kernel Machines, Recursive Neural Networks and Their Integration.
Proceedings of the Neural Nets, 14th Italian Workshop on Neural Nets, 2003

Multi-prototype Support Vector Machine.
Proceedings of the IJCAI-03, 2003

Formal Determination of Context in Contextual Recursive Cascade Correlation Networks.
Proceedings of the Artificial Neural Networks and Neural Information Processing, 2003

Discretizing Continuous Attributes in AdaBoost for Text Categorization.
Proceedings of the Advances in Information Retrieval, 2003

2002
Theoretical and Experimental Analysis of a Two-Stage System for Classification.
IEEE Trans. Pattern Anal. Mach. Intell., 2002

Special issue on integration of symbolic and connectionist systems.
Cogn. Syst. Res., 2002

A re-weighting strategy for improving margins.
Artif. Intell., 2002

An efficient SMO-like algorithm for multiclass SVM.
Proceedings of the 12th IEEE Workshop on Neural Networks for Signal Processing, 2002

On Linear Separability of Sequences and Structures.
Proceedings of the Artificial Neural Networks, 2002

A general framework for unsupervised processing of structured data.
Proceedings of the 10th Eurorean Symposium on Artificial Neural Networks, 2002

Learning and Solving Soft Temporal Constraints: An Experimental Study.
Proceedings of the Principles and Practice of Constraint Programming, 2002

2001
Guest Editors' Introduction: Special Section on Connectionist Models for Learning in Structured Domains.
IEEE Trans. Knowl. Data Eng., 2001

Analysis of the Internal Representations Developed by Neural Networks for Structures Applied to Quantitative Structure-Activity Relationship Studies of Benzodiazepines.
J. Chem. Inf. Comput. Sci., 2001

A Supervised Self-Organizing Map for Structured Data.
Proceedings of the Advances in Self-Organising Maps, 2001

Learning preferences on temporal constraints: a preliminary report.
Proceedings of the Eigth International Symposium on Temporal Representation and Reasoning, 2001

On the Need for a Neural Abstract Machine.
Proceedings of the Sequence Learning - Paradigms, Algorithms, and Applications, 2001

A Simple Additive Re-weighting Strategy for Improving Margins.
Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, 2001

Neural Networks for Adaptive Processing of Structured Data.
Proceedings of the Artificial Neural Networks, 2001

2000
Discriminant Pattern Recognition Using Transformation-Invariant Neurons.
Neural Comput., 2000

Application of Cascade Correlation Networks for Structures to Chemistry.
Appl. Intell., 2000

Experimental Results on Learning Soft Constraints.
Proceedings of the KR 2000, 2000

Bi-Causal Recurrent Cascade Correlation.
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000

Learning Efficiently with Neural Networks: A Theoretical Comparison between Structured and Flat Representations.
Proceedings of the ECAI 2000, 2000

An Improved Boosting Algorithm and its Application to Text Categorization.
Proceedings of the 2000 ACM CIKM International Conference on Information and Knowledge Management, 2000

A Neural-Based System for the Automatic Classification and Follow-Up of Diabetic Retinopathies.
Proceedings of the Artificial Neural Networks in Biomedicine, 2000

1999
On the implementation of frontier-to-root tree automata in recursive neural networks.
IEEE Trans. Neural Networks, 1999

Optical Font Recognition for Multi-Font OCR and Document Processing.
Proceedings of the 10th International Workshop on Database & Expert Systems Applications, 1999

1998
A general framework for adaptive processing of data structures.
IEEE Trans. Neural Networks, 1998

Learning solution preferences in constraint problems.
J. Exp. Theor. Artif. Intell., 1998

Rule Specialization in Networks of Fuzzy Basis Functions.
Intell. Autom. Soft Comput., 1998

Integration of Graphical Rules with Adaptive Learning of Structured Information.
Proceedings of the Hybrid Neural Systems, 1998

Some Experiments on Learning Soft Constraints.
Proceedings of the Principles and Practice of Constraint Programming, 1998

1997
Supervised neural networks for the classification of structures.
IEEE Trans. Neural Networks, 1997

On the Computational Power of Recurrent Neural Networks for Structures.
Neural Networks, 1997

Neural Networks for Processing Data Structures.
Proceedings of the Adaptive Processing of Sequences and Data Structures, 1997

On the Efficient Classification of Data Structures by Neural Networks.
Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, 1997

An overview on supervised neural networks for structures.
Proceedings of International Conference on Neural Networks (ICNN'97), 1997

Competitive and hybrid neuro-fuzzy models for supervised classification.
Proceedings of International Conference on Neural Networks (ICNN'97), 1997

Logo Recognition by Recursive Neural Networks.
Proceedings of the Graphics Recognition, 1997

1996
Extended Cascade-Correlation for Syntactic and Structural Pattern Recognition.
Proceedings of the Advances in Structural and Syntactical Pattern Recognition, 1996

A Constructive Learning Algorithm for Discriminant Tangent Models.
Proceedings of the Advances in Neural Information Processing Systems 9, 1996

A memory model based on LRAAM for associative access of structures.
Proceedings of International Conference on Neural Networks (ICNN'96), 1996

1995
Stability properties of labeling recursive auto-associative memory.
IEEE Trans. Neural Networks, 1995

Book Review: "Neural Network in Computer Intelligence", by LiMin Fu.
Int. J. Neural Syst., 1995

Learning Distributed Representations for the Classification of Terms.
Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, 1995

Modular Labeling RAAM.
Proceedings of the Artificial Neural Nets and Genetic Algorithms, 1995

1994
Labelling Recursive Auto-associative Memory.
Connect. Sci., 1994

A Rapid Graph-based Method for Arbitrary Transformation-Invariant Pattern Classification.
Proceedings of the Advances in Neural Information Processing Systems 7, 1994

1993
Speed up learning and network optimization with extended back propagation.
Neural Networks, 1993

Encoding Labeled Graphs by Labeling RAAM.
Proceedings of the Advances in Neural Information Processing Systems 6, 1993


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