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ORCIDAlessandro Sperduti
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- affiliation: University of Padua, Italy
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2020 – today
- 2025
[j68]Davide Rigoni, Nicolò Navarin, Alessandro Sperduti:
RGCVAE: relational graph conditioned variational autoencoder for molecule design. Mach. Learn. 114(1): 47 (2025)- 2024
- [j67]Giovanni Donghi
, Luca Pasa, Luca Oneto, Claudio Gallicchio, Alessio Micheli, Davide Anguita, Alessandro Sperduti, Nicolò Navarin:
Investigating over-parameterized randomized graph networks. Neurocomputing 606: 128281 (2024) - [j66]Luca Pasa, Nicolò Navarin, Wolfgang Erb, Alessandro Sperduti:
A unified framework for backpropagation-free soft and hard gated graph neural networks. Knowl. Inf. Syst. 66(4): 2393-2416 (2024) - [j65]Davide Rigoni, Luciano Serafini, Alessandro Sperduti:
Object search by a concept-conditioned object detector. Neural Comput. Appl. 36(26): 16001-16021 (2024) - [j64]Luca Pasa, Nicolò Navarin, Wolfgang Erb, Alessandro Sperduti:
Empowering Simple Graph Convolutional Networks. IEEE Trans. Neural Networks Learn. Syst. 35(4): 4385-4399 (2024) - [c152]Flavio Petruzzellis, Alberto Testolin, Alessandro Sperduti:
Benchmarking GPT-4 on Algorithmic Problems: A Systematic Evaluation of Prompting Strategies. LREC/COLING 2024: 2161-2177 - [c151]Muhammad Uzair-Ul-Haq, Davide Rigoni, Alessandro Sperduti:
Prompt-Based Data Augmentation Using Contrastive Learning Under Scarcity of Annotated Data. ECAI 2024: 2717-2724 - [c150]Samuel Cognolato, Alessandro Sperduti, Luciano Serafini:
IFH: A Diffusion Framework for Flexible Design of Graph Generative Models. ECAI 2024: 3039-3046 - [c149]Flavio Petruzzellis, Alberto Testolin, Alessandro Sperduti:
A Neural Rewriting System to Solve Algorithmic Problems. ECAI 2024: 3112-3119 - [c148]Nicolò Navarin, Luca Pasa, Alessandro Sperduti:
Towards the application of Backpropagation-Free Graph Convolutional Networks on Huge Datasets. ESANN 2024 - [c147]Flavio Petruzzellis, Alberto Testolin, Alessandro Sperduti:
Assessing the Emergent Symbolic Reasoning Abilities of Llama Large Language Models. ICANN (5) 2024: 266-276 - [c146]Giovanni Donghi, Luca Pasa, Alberto Testolin, Marco Zorzi, Alessandro Sperduti, Nicolò Navarin:
Relative Local Signal Strength: The Impact of Normalization on the Analysis of Neuroimaging Data with Deep Learning. ICANN (8) 2024: 373-383 - [c145]Nicolò Navarin, Paolo Frazzetto, Luca Pasa, Pietro Verzelli, Filippo Visentin, Alessandro Sperduti, Cesare Alippi:
Physics-Informed Graph Neural Cellular Automata: an Application to Compartmental Modelling. IJCNN 2024: 1-9 - [c144]Paolo Frazzetto, Luca Pasa, Nicolò Navarin, Alessandro Sperduti:
Beyond the Additive Nodes' Convolutions: a Study on High-Order Multiplicative Integration. SAC 2024: 474-481 - [c143]Muhammad Uzair-Ul-Haq, Paolo Frazzetto, Alessandro Sperduti, Giovanni Da San Martino:
Improving Soft Skill Extraction via Data Augmentation and Embedding Manipulation. SAC 2024: 987-996 - [e6]Nicola Bena, Beniamino Di Martino, Antonio Maratea, Alessandro Sperduti, Emanuel Di Nardo, Angelo Ciaramella, Raffaele Montella, Claudio A. Ardagna:
Proceedings of the 2nd Italian Conference on Big Data and Data Science (ITADATA 2023), Naples, Italy, September 11-13, 2023. CEUR Workshop Proceedings 3606, CEUR-WS.org 2024 [contents] - [i31]Flavio Petruzzellis, Alberto Testolin, Alessandro Sperduti:
Benchmarking GPT-4 on Algorithmic Problems: A Systematic Evaluation of Prompting Strategies. CoRR abs/2402.17396 (2024) - [i30]Flavio Petruzzellis, Alberto Testolin, Alessandro Sperduti:
A Neural Rewriting System to Solve Algorithmic Problems. CoRR abs/2402.17407 (2024) - [i29]Flavio Petruzzellis, Alberto Testolin, Alessandro Sperduti:
Assessing the Emergent Symbolic Reasoning Abilities of Llama Large Language Models. CoRR abs/2406.06588 (2024) - [i28]Samuel Cognolato, Alessandro Sperduti, Luciano Serafini:
IFH: a Diffusion Framework for Flexible Design of Graph Generative Models. CoRR abs/2408.13194 (2024) - 2023
- [c142]Davide Rigoni, Luca Parolari, Luciano Serafini, Alessandro Sperduti, Lamberto Ballan:
Weakly-Supervised Visual-Textual Grounding with Semantic Prior Refinement. BMVC 2023: 229 - [c141]Leonardo Amato, Marta Maschietto, Alessandro Leparulo, Mattia Tambaro, Stefano Vassanelli, Alessandro Sperduti:
Real-time Detection of Evoked Potentials by Deep Learning: a Case Study. ESANN 2023 - [c140]Nicolò Navarin, Luca Pasa, Luca Oneto, Alessandro Sperduti:
An Empirical Study of Over-Parameterized Neural Models based on Graph Random Features. ESANN 2023 - [c139]Nicolò Navarin, Luca Pasa, Claudio Gallicchio, Alessandro Sperduti:
An Untrained Neural Model for Fast and Accurate Graph Classification. ICANN (4) 2023: 278-290 - [c138]Paolo Frazzetto, Muhammad Uzair-Ul-Haq, Alessandro Sperduti:
Enhancing Human Resources through Data Science: a Case in Recruiting. itaDATA 2023 - [c137]Flavio Petruzzellis, Alberto Testolin, Alessandro Sperduti:
A Hybrid System for Systematic Generalization in Simple Arithmetic Problems. NeSy 2023: 289-301 - [c136]Paolo Frazzetto, Luca Pasa, Nicolò Navarin, Alessandro Sperduti:
Topology preserving maps as aggregations for Graph Convolutional Neural Networks. SAC 2023: 536-543 - [i27]Davide Rigoni, Luca Parolari, Luciano Serafini, Alessandro Sperduti, Lamberto Ballan:
Weakly-Supervised Visual-Textual Grounding with Semantic Prior Refinement. CoRR abs/2305.10913 (2023) - [i26]Davide Rigoni, Nicolò Navarin, Alessandro Sperduti:
RGCVAE: Relational Graph Conditioned Variational Autoencoder for Molecule Design. CoRR abs/2305.11699 (2023) - [i25]Flavio Petruzzellis, Alberto Testolin, Alessandro Sperduti:
A Hybrid System for Systematic Generalization in Simple Arithmetic Problems. CoRR abs/2306.17249 (2023) - 2022
- [j63]Marco Gori, Alessandro Sperduti, Piero P. Bonissone:
Conference Report on 2022 IEEE World Congress on Computational Intelligence (IEEE WCCI 2022). IEEE Comput. Intell. Mag. 17(4): 8-12 (2022) - [j62]Shahi Dost, Luciano Serafini, Marco Rospocher, Lamberto Ballan, Alessandro Sperduti:
Aligning and linking entity mentions in image, text, and knowledge base. Data Knowl. Eng. 138: 101975 (2022) - [j61]Luca Oneto, Nicolò Navarin, Battista Biggio, Federico Errica, Alessio Micheli, Franco Scarselli, Monica Bianchini, Luca Demetrio, Pietro Bongini, Armando Tacchella, Alessandro Sperduti:
Towards learning trustworthily, automatically, and with guarantees on graphs: An overview. Neurocomputing 493: 217-243 (2022) - [j60]Luca Pasa, Nicolò Navarin, Alessandro Sperduti:
Polynomial-based graph convolutional neural networks for graph classification. Mach. Learn. 111(4): 1205-1237 (2022) - [j59]Luca Pasa, Nicolò Navarin, Alessandro Sperduti:
SOM-based aggregation for graph convolutional neural networks. Neural Comput. Appl. 34(1): 5-24 (2022) - [j58]Luca Pasa, Nicolò Navarin, Alessandro Sperduti:
Multiresolution Reservoir Graph Neural Network. IEEE Trans. Neural Networks Learn. Syst. 33(6): 2642-2653 (2022) - [c135]Federico Caldart, Luca Pasa, Luca Oneto, Alessandro Sperduti, Nicolò Navarin:
Biased Edge Dropout in NIFTY for Fair Graph Representation Learning. ESANN 2022 - [c134]Luca Pasa, Nicolò Navarin, Wolfgang Erb, Alessandro Sperduti:
Backpropagation-free Graph Neural Networks. ICDM 2022: 388-397 - [c133]Davide Rigoni, Luciano Serafini, Alessandro Sperduti:
A better loss for visual-textual grounding. SAC 2022: 49-57 - [c132]Luca Pasa, Nicolò Navarin, Alessandro Sperduti:
Compact graph neural network models for node classification. SAC 2022: 592-599 - 2021
- [j57]Antonio Carta, Alessandro Sperduti, Davide Bacciu:
Encoding-based memory for recurrent neural networks. Neurocomputing 456: 407-420 (2021) - [c131]Luca Oneto, Nicolò Navarin, Battista Biggio, Federico Errica, Alessio Micheli, Franco Scarselli, Monica Bianchini, Alessandro Sperduti:
Complex Data: Learning Trustworthily, Automatically, and with Guarantees. ESANN 2021 - [c130]Luca Pasa, Nicolò Navarin, Alessandro Sperduti:
Tangent Graph Convolutional Network. ESANN 2021 - [c129]Valeria Orso, Daniele Verì, Riccardo Minato, Alessandro Sperduti, Luciano Gamberini:
Are Professional Kitchens Ready for Dummies? A Comparative Usability Evaluation Between Expert and Non-expert Users. HCI (3) 2021: 418-428 - [c128]Yunrui Guo, Guglielmo Camporese, Wenjing Yang, Alessandro Sperduti, Lamberto Ballan:
Conditional Variational Capsule Network for Open Set Recognition. ICCV 2021: 103-111 - [c127]Luca Pasa, Nicolò Navarin, Alessandro Sperduti:
Simple Multi-resolution Gated GNN. SSCI 2021: 1-7 - [i24]Yunrui Guo, Guglielmo Camporese, Wenjing Yang, Alessandro Sperduti, Lamberto Ballan:
Conditional Variational Capsule Network for Open Set Recognition. CoRR abs/2104.09159 (2021) - [i23]Luca Pasa, Nicolò Navarin, Wolfgang Erb, Alessandro Sperduti:
Simple Graph Convolutional Networks. CoRR abs/2106.05809 (2021) - [i22]Davide Rigoni, Luciano Serafini, Alessandro Sperduti:
A Better Loss for Visual-Textual Grounding. CoRR abs/2108.05308 (2021) - 2020
- [j56]Dinh Van Tran, Alessandro Sperduti, Rolf Backofen, Fabrizio Costa:
Heterogeneous networks integration for disease-gene prioritization with node kernels. Bioinform. 36(9): 2649-2656 (2020) - [j55]Luca Oneto, Kerstin Bunte, Alessandro Sperduti:
Advances in artificial neural networks, machine learning and computational intelligence. Neurocomputing 416: 172-176 (2020) - [j54]Nicolò Navarin, Dinh Tran-Van, Alessandro Sperduti:
A framework for the definition of complex structured feature spaces. Neurocomputing 416: 190-201 (2020) - [j53]Manuel Dorado-Moreno, Nicolò Navarin, Pedro Antonio Gutiérrez, Luis Prieto, Alessandro Sperduti, Sancho Salcedo-Sanz, César Hervás-Martínez:
Multi-task learning for the prediction of wind power ramp events with deep neural networks. Neural Networks 123: 401-411 (2020) - [c126]Nicolò Navarin, Dinh Van Tran, Alessandro Sperduti:
Learning Kernel-Based Embeddings in Graph Neural Networks. ECAI 2020: 1387-1394 - [c125]Shahi Dost, Luciano Serafini, Marco Rospocher, Lamberto Ballan, Alessandro Sperduti:
VT-LINKER: Visual-Textual-Knowledge Entity Linker. ECAI 2020: 2897-2898 - [c124]Nicolò Navarin, Wolfgang Erb, Luca Pasa, Alessandro Sperduti:
Linear Graph Convolutional Networks. ESANN 2020: 151-156 - [c123]Luca Pasa, Nicolò Navarin, Alessandro Sperduti:
Deep Recurrent Graph Neural Networks. ESANN 2020: 157-162 - [c122]Davide Rigoni, Nicolò Navarin, Alessandro Sperduti:
A Systematic Assessment of Deep Learning Models for Molecule Generation. ESANN 2020: 547-552 - [c121]Nicolò Navarin, Matteo Cambiaso, Andrea Burattin, Fabrizio Maria Maggi, Luca Oneto, Alessandro Sperduti:
Towards Online Discovery of Data-Aware Declarative Process Models from Event Streams. IJCNN 2020: 1-8 - [c120]Shahi Dost, Luciano Serafini, Marco Rospocher, Lamberto Ballan, Alessandro Sperduti:
Jointly Linking Visual and Textual Entity Mentions with Background Knowledge. NLDB 2020: 264-276 - [c119]Antonio Carta, Alessandro Sperduti, Davide Bacciu:
Incremental Training of a Recurrent Neural Network Exploiting a Multi-scale Dynamic Memory. ECML/PKDD (1) 2020: 677-693 - [c118]Shahi Dost, Luciano Serafini, Marco Rospocher, Lamberto Ballan, Alessandro Sperduti:
VTKEL: a resource for visual-textual-knowledge entity linking. SAC 2020: 2021-2028 - [c117]Shahi Dost, Luciano Serafini, Marco Rospocher, Lamberto Ballan, Alessandro Sperduti:
On Visual-Textual-Knowledge Entity Linking. ICSC 2020: 190-193 - [c116]Davide Rigoni, Nicolò Navarin, Alessandro Sperduti:
Conditional Constrained Graph Variational Autoencoders for Molecule Design. SSCI 2020: 729-736 - [e5]Luca Oneto, Nicolò Navarin, Alessandro Sperduti, Davide Anguita:
Recent Advances in Big Data and Deep Learning, Proceedings of the INNS Big Data and Deep Learning Conference INNSBDDL 2019, held at Sestri Levante, Genova, Italy 16-18 April 2019. Springer 2020, ISBN 978-3-030-16840-7 [contents] - [e4]Luca Oneto, Nicolò Navarin, Alessandro Sperduti, Davide Anguita:
Recent Trends in Learning From Data - Tutorials from the INNS Big Data and Deep Learning Conference (INNSBDDL 2019). Studies in Computational Intelligence 896, Springer 2020, ISBN 978-3-030-43882-1 [contents] - [i21]Antonio Carta, Alessandro Sperduti, Davide Bacciu:
Encoding-based Memory Modules for Recurrent Neural Networks. CoRR abs/2001.11771 (2020) - [i20]Antonio Carta, Alessandro Sperduti, Davide Bacciu:
Incremental Training of a Recurrent Neural Network Exploiting a Multi-Scale Dynamic Memory. CoRR abs/2006.16800 (2020) - [i19]Davide Rigoni, Nicolò Navarin, Alessandro Sperduti:
A Systematic Assessment of Deep Learning Models for Molecule Generation. CoRR abs/2008.09168 (2020) - [i18]Davide Rigoni, Nicolò Navarin, Alessandro Sperduti:
Conditional Constrained Graph Variational Autoencoders for Molecule Design. CoRR abs/2009.00725 (2020) - [i17]Antonio Carta, Alessandro Sperduti, Davide Bacciu:
Short-Term Memory Optimization in Recurrent Neural Networks by Autoencoder-based Initialization. CoRR abs/2011.02886 (2020)
2010 – 2019
- 2019
- [j52]Anna A. Kalenkova, Andrea Burattin, Massimiliano de Leoni, Wil M. P. van der Aalst, Alessandro Sperduti:
Discovering high-level BPMN process models from event data. Bus. Process. Manag. J. 25(5): 995-1019 (2019) - [c115]Giovanni Da San Martino, Alessandro Sperduti, Fabio Aiolli, Alessandro Moschitti:
Efficient Online Learning for Mapping Kernels on Linguistic Structures. AAAI 2019: 3421-3428 - [c114]Nicolò Navarin, Dinh Van Tran, Alessandro Sperduti:
On the definition of complex structured feature spaces. ESANN 2019 - [c113]Benjamin Paaßen, Claudio Gallicchio, Alessio Micheli, Alessandro Sperduti:
Embeddings and Representation Learning for Structured Data. ESANN 2019 - [c112]Davide Bacciu, Antonio Carta, Alessandro Sperduti:
Linear Memory Networks. ICANN (1) 2019: 513-525 - [c111]Nicolò Navarin, Dinh Van Tran, Alessandro Sperduti:
Universal Readout for Graph Convolutional Neural Networks. IJCNN 2019: 1-7 - [c110]Luca Oneto, Nicolò Navarin, Alessandro Sperduti, Davide Anguita:
Introduction. INNSBDDL (Tutorials) 2019: 1-4 - [c109]Valeria Orso, Alessandro Sperduti, Luciano Gamberini:
Integrating kitchen appliances to improve food quality and sustainability: the SIAF project. PETRA 2019: 311-312 - [i16]Benjamin Paaßen, Claudio Gallicchio, Alessio Micheli, Alessandro Sperduti:
Embeddings and Representation Learning for Structured Data. CoRR abs/1905.06147 (2019) - 2018
- [j51]Guido Zampieri, Dinh Tran-Van, Michele Donini, Nicolò Navarin, Fabio Aiolli, Alessandro Sperduti, Giorgio Valle:
Scuba: scalable kernel-based gene prioritization. BMC Bioinform. 19(1): 23:1-23:12 (2018) - [j50]Mirko Polato, Alessandro Sperduti, Andrea Burattin, Massimiliano de Leoni:
Time and activity sequence prediction of business process instances. Computing 100(9): 1005-1031 (2018) - [j49]Dinh Tran-Van, Alessandro Sperduti, Fabrizio Costa:
The conjunctive disjunctive graph node kernel for disease gene prioritization. Neurocomputing 298: 90-99 (2018) - [j48]Luca Oneto, Nicolò Navarin, Alessandro Sperduti, Davide Anguita:
Multilayer Graph Node Kernels: Stacking While Maintaining Convexity. Neural Process. Lett. 48(2): 649-667 (2018) - [j47]Giovanni Da San Martino, Nicolò Navarin, Alessandro Sperduti:
Tree-Based Kernel for Graphs With Continuous Attributes. IEEE Trans. Neural Networks Learn. Syst. 29(7): 3270-3276 (2018) - [j46]Luca Oneto, Nicolò Navarin, Michele Donini, Sandro Ridella, Alessandro Sperduti, Fabio Aiolli, Davide Anguita:
Learning With Kernels: A Local Rademacher Complexity-Based Analysis With Application to Graph Kernels. IEEE Trans. Neural Networks Learn. Syst. 29(10): 4660-4671 (2018) - [j45]Davide Bacciu, Alessio Micheli, Alessandro Sperduti:
Generative Kernels for Tree-Structured Data. IEEE Trans. Neural Networks Learn. Syst. 29(10): 4932-4946 (2018) - [c108]Dinh Tran-Van, Nicolò Navarin, Alessandro Sperduti:
DEEP: decomposition feature enhancement procedure for graphs. ESANN 2018 - [c107]Nicolò Navarin, Giovanni Da San Martino, Alessandro Sperduti:
Extreme Graph Kernels for Online Learning on a Memory Budget. IJCNN 2018: 1-8 - [c106]Dinh Van Tran, Nicolò Navarin, Alessandro Sperduti:
On Filter Size in Graph Convolutional Networks. SSCI 2018: 1534-1541 - [i15]Davide Bacciu, Antonio Carta, Alessandro Sperduti:
Linear Memory Networks. CoRR abs/1811.03356 (2018) - [i14]Nicolò Navarin, Dinh Van Tran, Alessandro Sperduti:
Pre-training Graph Neural Networks with Kernels. CoRR abs/1811.06930 (2018) - [i13]Dinh Van Tran, Nicolò Navarin, Alessandro Sperduti:
On Filter Size in Graph Convolutional Networks. CoRR abs/1811.10435 (2018) - 2017
- [j44]Luca Oneto, Nicolò Navarin, Michele Donini, Alessandro Sperduti, Fabio Aiolli, Davide Anguita:
Measuring the expressivity of graph kernels through Statistical Learning Theory. Neurocomputing 268: 4-16 (2017) - [c105]Nicolò Navarin, Alessandro Sperduti:
Approximated Neighbours MinHash Graph Node Kernel. ESANN 2017 - [c104]Dinh Tran-Van, Alessandro Sperduti, Fabrizio Costa:
The Conjunctive Disjunctive Node Kernel. ESANN 2017 - [c103]Dinh Tran-Van, Alessandro Sperduti, Fabrizio Costa:
Link Enrichment for Diffusion-Based Graph Node Kernels. ICANN (2) 2017: 155-162 - [c102]Dinh Tran-Van, Alessandro Sperduti, Fabrizio Costa:
Joint Neighborhood Subgraphs Link Prediction. ICONIP (1) 2017: 117-123 - [c101]Luca Oneto, Nicolò Navarin, Alessandro Sperduti, Davide Anguita:
Deep graph node kernels: A convex approach. IJCNN 2017: 316-323 - [c100]Luca Pasa, Alessandro Sperduti, Peter Tiño:
Linear dynamical based models for sequential domains. IJCNN 2017: 2201-2208 - [c99]Valerio Grossi, Alessandro Sperduti:
A kernel-based ensemble classifier for evolving stream of trees with double concept drifting reaction. IJCNN 2017: 3975-3982 - [c98]Nicolò Navarin, Beatrice Vincenzi, Mirko Polato, Alessandro Sperduti:
LSTM networks for data-aware remaining time prediction of business process instances. SSCI 2017: 1-7 - [i12]Nicolò Navarin, Beatrice Vincenzi, Mirko Polato, Alessandro Sperduti:
LSTM Networks for Data-Aware Remaining Time Prediction of Business Process Instances. CoRR abs/1711.03822 (2017) - 2016
- [j43]Alberto Testolin, Ivilin Peev Stoianov, Alessandro Sperduti, Marco Zorzi:
Learning Orthographic Structure With Sequential Generative Neural Networks. Cogn. Sci. 40(3): 579-606 (2016) - [j42]Andrea Burattin, Fabrizio Maria Maggi, Alessandro Sperduti:
Conformance checking based on multi-perspective declarative process models. Expert Syst. Appl. 65: 194-211 (2016) - [j41]Giovanni Da San Martino, Nicolò Navarin, Alessandro Sperduti:
Ordered Decompositional DAG kernels enhancements. Neurocomputing 192: 92-103 (2016) - [j40]Giovanni Da San Martino, Nicolò Navarin, Alessandro Sperduti:
An empirical study on budget-aware online kernel algorithms for streams of graphs. Neurocomputing 216: 163-182 (2016) - [c97]Luca Pasa, Alessandro Sperduti:
Learning Sequential Data with the Help of Linear Systems. ANNPR 2016: 3-17 - [c96]Plamen Angelov, Alessandro Sperduti:
Challenges in Deep Learning. ESANN 2016 - [c95]Luca Oneto, Nicolò Navarin, Michele Donini, Alessandro Sperduti, Fabio Aiolli, Davide Anguita:
Measuring the Expressivity of Graph Kernels through the Rademacher Complexity. ESANN 2016 - [c94]Carlo M. Massimo, Nicolò Navarin, Alessandro Sperduti:
Hyper-Parameter Tuning for Graph Kernels via Multiple Kernel Learning. ICONIP (2) 2016: 214-223 - [c93]Hossein Fereidooni, Mauro Conti, Danfeng Yao, Alessandro Sperduti:
ANASTASIA: ANdroid mAlware detection using STatic analySIs of Applications. NTMS 2016: 1-5 - [i11]Mirko Polato, Alessandro Sperduti, Andrea Burattin, Massimiliano de Leoni:
Time and Activity Sequence Prediction of Business Process Instances. CoRR abs/1602.07566 (2016) - 2015
- [j39]Luca Pasa, Alberto Testolin, Alessandro Sperduti:
Neural Networks for Sequential Data: a Pre-training Approach based on Hidden Markov Models. Neurocomputing 169: 323-333 (2015) - [j38]Fabio Aiolli, Giovanni Da San Martino, Alessandro Sperduti:
An Efficient Topological Distance-Based Tree Kernel. IEEE Trans. Neural Networks Learn. Syst. 26(5): 1115-1120 (2015) - [j37]Andrea Burattin, Marta Cimitile, Fabrizio Maria Maggi, Alessandro Sperduti:
Online Discovery of Declarative Process Models from Event Streams. IEEE Trans. Serv. Comput. 8(6): 833-846 (2015) - [c92]Giovanni Da San Martino, Nicolò Navarin, Alessandro Sperduti:
Exploiting the ODD framework to define a novel effective graph kernel. ESANN 2015 - [c91]Nicolò Navarin, Alessandro Sperduti, Riccardo Tesselli:
Extending Local Features with Contextual Information in Graph Kernels. ICONIP (4) 2015: 271-279 - [c90]Alessandro Sperduti:
Equivalence Results between Feedforward and Recurrent Neural Networks for Sequences. IJCAI 2015: 3827-3833 - [c89]Fabio Aiolli, Michele Donini, Nicolò Navarin, Alessandro Sperduti:
Multiple Graph-Kernel Learning. SSCI 2015: 1607-1614 - [p6]Peter Tiño, Lubica Benuskova, Alessandro Sperduti:
Artificial Neural Network Models. Handbook of Computational Intelligence 2015: 455-471 - [p5]Davide Bacciu, Paulo J. G. Lisboa, Alessandro Sperduti, Thomas Villmann:
Probabilistic Modeling in Machine Learning. Handbook of Computational Intelligence 2015: 545-575 - [i10]Andrea Burattin, Fabrizio Maria Maggi, Alessandro Sperduti:
Conformance Checking Based on Multi-Perspective Declarative Process Models. CoRR abs/1503.04957 (2015) - [i9]Giovanni Da San Martino, Nicolò Navarin, Alessandro Sperduti:
An Empirical Study on Budget-Aware Online Kernel Algorithms for Streams of Graphs. CoRR abs/1507.02158 (2015) - [i8]Nicolò Navarin, Alessandro Sperduti, Riccardo Tesselli:
Extending local features with contextual information in graph kernels. CoRR abs/1507.02186 (2015) - [i7]Giovanni Da San Martino, Nicolò Navarin, Alessandro Sperduti:
Ordered Decompositional DAG Kernels Enhancements. CoRR abs/1507.03372 (2015) - [i6]Giovanni Da San Martino, Nicolò Navarin, Alessandro Sperduti:
A tree-based kernel for graphs with continuous attributes. CoRR abs/1509.01116 (2015) - [i5]Giovanni Da San Martino, Nicolò Navarin, Alessandro Sperduti:
Graph Kernels exploiting Weisfeiler-Lehman Graph Isomorphism Test Extensions. CoRR abs/1509.06589 (2015) - 2014
- [c88]Andrea Burattin, Alessandro Sperduti, Wil M. P. van der Aalst:
Control-flow discovery from event streams. IEEE Congress on Evolutionary Computation 2014: 2420-2427 - [c87]Alessandro Berti, Alessandro Sperduti, Andrea Burattin:
A novel criterion for overlapping communities detection and clustering improvement. CIDM 2014: 249-256 - [c86]Luca Pasa, Alberto Testolin, Alessandro Sperduti:
A HMM-based pre-training approach for sequential data. ESANN 2014 - [c85]Giovanni Da San Martino, Nicolò Navarin, Alessandro Sperduti:
Graph Kernels Exploiting Weisfeiler-Lehman Graph Isomorphism Test Extensions. ICONIP (2) 2014: 93-100 - [c84]Davide Bacciu, Alessio Micheli, Alessandro Sperduti:
Modeling Bi-directional Tree Contexts by Generative Transductions. ICONIP (1) 2014: 543-550 - [c83]Mirko Polato, Alessandro Sperduti, Andrea Burattin, Massimiliano de Leoni:
Data-aware remaining time prediction of business process instances. IJCNN 2014: 816-823 - [c82]Davide Bacciu, Alessio Micheli, Alessandro Sperduti:
Integrating bi-directional contexts in a generative kernel for trees. IJCNN 2014: 4145-4151 - [c81]Luca Pasa, Alessandro Sperduti:
Pre-training of Recurrent Neural Networks via Linear Autoencoders. NIPS 2014: 3572-3580 - 2013
- [j36]Davide Bacciu, Alessio Micheli, Alessandro Sperduti:
An input-output hidden Markov model for tree transductions. Neurocomputing 112: 34-46 (2013) - [j35]Davide Bacciu, Alessio Micheli, Alessandro Sperduti:
Compositional Generative Mapping for Tree-Structured Data - Part II: Topographic Projection Model. IEEE Trans. Neural Networks Learn. Syst. 24(2): 231-247 (2013) - [c80]Andrea Burattin, Alessandro Sperduti, Marco Veluscek:
Business models enhancement through discovery of roles. CIDM 2013: 103-110 - [c79]Giovanni Da San Martino, Nicolò Navarin, Alessandro Sperduti:
A Lossy Counting Based Approach for Learning on Streams of Graphs on a Budget. IJCAI 2013: 1294-1301 - [c78]Fabrizio Maria Maggi, Andrea Burattin, Marta Cimitile, Alessandro Sperduti:
Online Process Discovery to Detect Concept Drifts in LTL-Based Declarative Process Models. OTM Conferences 2013: 94-111 - 2012
- [j34]Davide Bacciu, Alessio Micheli, Alessandro Sperduti:
Compositional Generative Mapping for Tree-Structured Data - Part I: Bottom-Up Probabilistic Modeling of Trees. IEEE Trans. Neural Networks Learn. Syst. 23(12): 1987-2002 (2012) - [c77]Andrea Burattin, Fabrizio Maria Maggi, Wil M. P. van der Aalst, Alessandro Sperduti:
Techniques for a Posteriori Analysis of Declarative Processes. EDOC 2012: 41-50 - [c76]Davide Bacciu, Alessio Micheli, Alessandro Sperduti:
Input-Output Hidden Markov Models for trees. ESANN 2012 - [c75]Alberto Testolin, Alessandro Sperduti, Ivilin Peev Stoianov, Marco Zorzi:
Assessment of sequential Boltmann machines on a lexical processing task. ESANN 2012 - [c74]Davide Bacciu, Alessio Micheli, Alessandro Sperduti:
A Generative Multiset Kernel for Structured Data. ICANN (1) 2012: 57-64 - [c73]Giovanni Da San Martino, Nicolò Navarin, Alessandro Sperduti:
A memory efficient graph kernel. IJCNN 2012: 1-7 - [c72]Giovanni Da San Martino, Nicolò Navarin, Alessandro Sperduti:
A Tree-Based Kernel for Graphs. SDM 2012: 975-986 - [i4]Andrea Burattin, Alessandro Sperduti, Wil M. P. van der Aalst:
Heuristics Miners for Streaming Event Data. CoRR abs/1212.6383 (2012) - 2011
- [c71]Fabio Aiolli, Andrea Burattin, Alessandro Sperduti:
A Business Process Metric Based on the Alpha Algorithm Relations. Business Process Management Workshops (1) 2011: 141-146 - [c70]Wil M. P. van der Aalst, Arya Adriansyah, Ana Karla Alves de Medeiros, Franco Arcieri, Thomas Baier, Tobias Blickle, R. P. Jagadeesh Chandra Bose, Peter van den Brand, Ronald Brandtjen, Joos C. A. M. Buijs, Andrea Burattin, Josep Carmona, Malú Castellanos, Jan Claes, Jonathan E. Cook, Nicola Costantini, Francisco Curbera, Ernesto Damiani, Massimiliano de Leoni, Pavlos Delias, Boudewijn F. van Dongen, Marlon Dumas, Schahram Dustdar, Dirk Fahland, Diogo R. Ferreira, Walid Gaaloul, Frank van Geffen, Sukriti Goel, Christian W. Günther, Antonella Guzzo, Paul Harmon, Arthur H. M. ter Hofstede, John Hoogland, Jon Espen Ingvaldsen, Koki Kato, Rudolf Kuhn, Akhil Kumar, Marcello La Rosa, Fabrizio Maria Maggi, Donato Malerba, R. S. Mans, Alberto Manuel, Martin McCreesh, Paola Mello, Jan Mendling, Marco Montali, Hamid R. Motahari Nezhad, Michael zur Muehlen, Jorge Munoz-Gama, Luigi Pontieri, Joel Ribeiro, Anne Rozinat, Hugo Seguel Pérez, Ricardo Seguel Pérez, Marcos Sepúlveda, Jim Sinur, Pnina Soffer, Minseok Song, Alessandro Sperduti, Giovanni Stilo, Casper Stoel, Keith D. Swenson, Maurizio Talamo, Wei Tan, Chris Turner, Jan Vanthienen, George Varvaressos, Eric Verbeek, Marc Verdonk, Roberto Vigo, Jianmin Wang, Barbara Weber, Matthias Weidlich, Ton Weijters, Lijie Wen, Michael Westergaard, Moe Thandar Wynn:
Process Mining Manifesto. Business Process Management Workshops (1) 2011: 169-194 - [c69]Markus Hagenbuchner, Giovanni Da San Martino, Ah Chung Tsoi, Alessandro Sperduti:
Sparsity Issues in Self-Organizing-Maps for Structures. ESANN 2011 - [c68]Fabio Aiolli, Giovanni Da San Martino, Alessandro Sperduti:
Extending Tree Kernels with Topological Information. ICANN (1) 2011: 142-149 - [c67]Valerio Grossi, Alessandro Sperduti:
Kernel-Based Selective Ensemble Learning for Streams of Trees. IJCAI 2011: 1281-1287 - [c66]Davide Bacciu, Alessio Micheli, Alessandro Sperduti:
Adaptive tree kernel by multinomial generative topographic mapping. IJCNN 2011: 1651-1658 - [c65]Claudio Guidi, Alessandro Sperduti:
Reasoning about service oriented recursion. SOCA 2011: 1-8 - [i3]Michael Biehl, Barbara Hammer, Erzsébet Merényi, Alessandro Sperduti, Thomas Villmann:
Learning in the context of very high dimensional data (Dagstuhl Seminar 11341). Dagstuhl Reports 1(8): 67-95 (2011) - 2010
- [j33]Giovanni Da San Martino, Alessandro Sperduti:
Mining Structured Data. IEEE Comput. Intell. Mag. 5(1): 42-49 (2010) - [c64]Andrea Burattin, Alessandro Sperduti:
PLG: A Framework for the Generation of Business Process Models and Their Execution Logs. Business Process Management Workshops 2010: 214-219 - [c63]Andrea Burattin, Alessandro Sperduti:
Automatic determination of parameters' values for Heuristics Miner++. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c62]Andrea Burattin, Alessandro Sperduti:
Heuristics Miner for Time Intervals. ESANN 2010 - [c61]Fabio Aiolli, Giovanni Da San Martino, Alessandro Sperduti:
A New Tree Kernel Based on SOM-SD. ICANN (2) 2010: 49-58 - [c60]Davide Bacciu, Alessio Micheli, Alessandro Sperduti:
Bottom-Up Generative Modeling of Tree-Structured Data. ICONIP (1) 2010: 660-668 - [c59]Davide Bacciu, Alessio Micheli, Alessandro Sperduti:
Compositional generative mapping of structured data. IJCNN 2010: 1-8 - [p4]Fabio Aiolli, Alessandro Sperduti:
A Preference Optimization Based Unifying Framework for Supervised Learning Problems. Preference Learning 2010: 19-42
2000 – 2009
- 2009
- [j32]Markus Hagenbuchner, Alessandro Sperduti, Ah Chung Tsoi:
Graph self-organizing maps for cyclic and unbounded graphs. Neurocomputing 72(7-9): 1419-1430 (2009) - [j31]Fabio Aiolli, Riccardo Cardin, Fabrizio Sebastiani, Alessandro Sperduti:
Preferential text classification: learning algorithms and evaluation measures. Inf. Retr. 12(5): 559-580 (2009) - [j30]Fabio Aiolli, Giovanni Da San Martino, Markus Hagenbuchner, Alessandro Sperduti:
Learning Nonsparse Kernels by Self-Organizing Maps for Structured Data. IEEE Trans. Neural Networks 20(12): 1938-1949 (2009) - [c58]Fabio Aiolli, Michele De Filippo De Grazia, Alessandro Sperduti:
Application of the preference learning model to a human resources selection task. CIDM 2009: 203-210 - [c57]Fabio Aiolli, Alessandro Sperduti:
Supervised learning as preference optimization. ESANN 2009 - [c56]Markus Hagenbuchner, Shujia Zhang, Ah Chung Tsoi, Alessandro Sperduti:
Projection of undirected and non-positional graphs using Self Organizing Maps. ESANN 2009 - [c55]Riccardo Cardin, Lisa Michielan, Stefano Moro, Alessandro Sperduti:
PCA-Based Representations of Graphs for Prediction in QSAR Studies. ICANN (2) 2009: 105-114 - [c54]Fabio Aiolli, Giovanni Da San Martino, Alessandro Sperduti:
Route kernels for trees. ICML 2009: 17-24 - [p3]Fabio Aiolli, Giovanni Da San Martino, Markus Hagenbuchner, Alessandro Sperduti:
Self-Organizing Maps for Structured Domains: Theory, Models, and Learning of Kernels. Innovations in Neural Information Paradigms and Applications 2009: 9-42 - [e3]Francesco Masulli, Alessio Micheli, Alessandro Sperduti:
Computational Intelligence and Bioengineering - Essays in Memory of Antonina Starita. Frontiers in Artificial Intelligence and Applications 196, IOS Press 2009, ISBN 978-1-60750-010-0 [contents] - [i2]Fabio Aiolli, Riccardo Cardin, Fabrizio Sebastiani, Alessandro Sperduti:
Preferential Text Classification: Learning Algorithms and Evaluation Measures. ERCIM News 2009(76) (2009) - 2008
- [c53]Markus Hagenbuchner, Alessandro Sperduti, Ah Chung Tsoi:
Self-Organizing Maps for cyclic and unbounded graphs. ESANN 2008: 203-208 - [c52]Fabio Aiolli, Giovanni Da San Martino, Alessandro Sperduti:
A Kernel Method for the Optimization of the Margin Distribution. ICANN (1) 2008: 305-314 - [c51]Shujia Zhang, Markus Hagenbuchner, Ah Chung Tsoi, Alessandro Sperduti:
Self Organizing Maps for the Clustering of Large Sets of Labeled Graphs. INEX 2008: 469-481 - 2007
- [j29]Lina Khatib, Paul H. Morris, Robert A. Morris, Francesca Rossi, Alessandro Sperduti, Kristen Brent Venable:
Solving and learning a tractable class of soft temporal constraints: Theoretical and experimental results. AI Commun. 20(3): 181-209 (2007) - [c50]Fabio Aiolli, Giovanni Da San Martino, Alessandro Sperduti, Alessandro Moschitti:
Efficient Kernel-based Learning for Trees. CIDM 2007: 308-315 - [c49]Alessandro Sperduti:
Efficient Computation of Recursive Principal Component Analysis for Structured Input. ECML 2007: 335-346 - [c48]Fabio Aiolli, Giovanni Da San Martino, Alessandro Sperduti, Markus Hagenbuchner:
"Kernelized" Self-Organizing Maps for Structured Data. ESANN 2007: 19-24 - [c47]Alessio Micheli, Alessandro Sperduti:
Recursive Principal Component Analysis of Graphs. ICANN (2) 2007: 826-835 - [c46]Fabio Aiolli, Fabrizio Sebastiani, Alessandro Sperduti:
Preference Learning for Category-Ranking based Interactive Text Categorization. IJCNN 2007: 2034-2039 - [c45]Markus Hagenbuchner, Ah Chung Tsoi, Alessandro Sperduti, Milly Kc:
Efficient Clustering of Structured Documents Using Graph Self-Organizing Maps. INEX 2007: 207-221 - [p2]Barbara Hammer, Alessio Micheli, Alessandro Sperduti:
Adaptive Contextual Processing of Structured Data by Recursive Neural Networks: A Survey of Computational Properties. Perspectives of Neural-Symbolic Integration 2007: 67-94 - [i1]Barbara Hammer, Alessio Micheli, Alessandro Sperduti:
A general framework for unsupervised preocessing of structured data. Probabilistic, Logical and Relational Learning - A Further Synthesis 2007 - 2006
- [j28]Paolo Frasconi, Alessandro Sperduti, Antonina Starita:
Kernel Machines, Neural Networks, and Graphical Models. Intelligenza Artificiale 3(1-2): 72-78 (2006) - [j27]Luca Bernazzani, Celia Duce, Alessio Micheli, Vincenzo Mollica, Alessandro Sperduti, Antonina Starita, Maria Rosaria Tiné:
Predicting Physical-Chemical Properties of Compounds from Molecular Structures by Recursive Neural Networks. J. Chem. Inf. Model. 46(5): 2030-2042 (2006) - [c44]Ah Chung Tsoi, Markus Hagenbuchner, Alessandro Sperduti:
Self-organising Map Techniques for Graph Data Applications to Clustering of XML Documents. ADMA 2006: 19-30 - [c43]Jochen J. Steil, Risto Kõiva, Alessandro Sperduti:
Unsupervised clustering of continuous trajectories of kinematic trees with SOM-SD. ESANN 2006: 1-6 - [c42]Alessandro Sperduti:
Exact Solutions for Recursive Principal Components Analysis of Sequences and Trees. ICANN (1) 2006: 349-356 - [c41]Fabio Aiolli, Giovanni Da San Martino, Alessandro Sperduti, Alessandro Moschitti:
Fast On-line Kernel Learning for Trees. ICDM 2006: 787-791 - [c40]Francesca Trentini, Markus Hagenbuchner, Alessandro Sperduti, Franco Scarselli:
A Self-Organising Map Approach for Clustering of XML Documents. IJCNN 2006: 1805-1812 - [c39]Milly Kc, Markus Hagenbuchner, Ah Chung Tsoi, Franco Scarselli, Alessandro Sperduti, Marco Gori:
XML Document Mining Using Contextual Self-organizing Maps for Structures. INEX 2006: 510-524 - 2005
- [j26]Alessio Micheli, Filippo Portera, Alessandro Sperduti:
A preliminary empirical comparison of recursive neural networks and tree kernel methods on regression tasks for tree structured domains. Neurocomputing 64: 73-92 (2005) - [j25]Fabio Aiolli, Alessandro Sperduti:
Multiclass Classification with Multi-Prototype Support Vector Machines. J. Mach. Learn. Res. 6: 817-850 (2005) - [j24]Barbara Hammer, Alessio Micheli, Alessandro Sperduti:
Universal Approximation Capability of Cascade Correlation for Structures. Neural Comput. 17(5): 1109-1159 (2005) - [j23]Barbara Hammer, Craig Saunders, Alessandro Sperduti:
Special issue on neural networks and kernel methods for structured domains. Neural Networks 18(8): 1015-1018 (2005) - [j22]Marco Gori, Alessandro Sperduti:
The loading problem for recursive neural networks. Neural Networks 18(8): 1064-1079 (2005) - [c38]Markus Hagenbuchner, Alessandro Sperduti, Ah Chung Tsoi:
Contextual Processing of Graphs using Self-Organizing Maps. ESANN 2005: 399-404 - [c37]Markus Hagenbuchner, Alessandro Sperduti, Ah Chung Tsoi, Francesca Trentini, Franco Scarselli, Marco Gori:
Clustering XML Documents Using Self-organizing Maps for Structures. INEX 2005: 481-496 - 2004
- [j21]Francesca Rossi, Alessandro Sperduti:
Acquiring Both Constraint and Solution Preferences in Interactive Constraint Systems. Constraints An Int. J. 9(4): 311-332 (2004) - [j20]Barbara Hammer, Alessio Micheli, Alessandro Sperduti, Marc Strickert:
A general framework for unsupervised processing of structured data. Neurocomputing 57: 3-35 (2004) - [j19]Barbara Hammer, Alessio Micheli, Alessandro Sperduti, Marc Strickert:
Recursive self-organizing network models. Neural Networks 17(8-9): 1061-1085 (2004) - [j18]Alessio Micheli, Diego Sona, Alessandro Sperduti:
Contextual processing of structured data by recursive cascade correlation. IEEE Trans. Neural Networks 15(6): 1396-1410 (2004) - [c36]Filippo Portera, Alessandro Sperduti:
A Generalized Quadratic Loss for Support Vector Machines. ECAI 2004: 628-634 - [c35]Alessio Micheli, Filippo Portera, Alessandro Sperduti:
A preliminary experimental comparison of recursive neural networks and a tree kernel method for QSAR/QSPR regression tasks. ESANN 2004: 293-298 - [c34]Fabio Aiolli, Alessandro Sperduti:
Learning Preferences for Multiclass Problems. NIPS 2004: 17-24 - [c33]Filippo Portera, Alessandro Sperduti:
Support Vector Regression with a Generalized Quadratic Loss. WIRN 2004: 209-216 - 2003
- [j17]Markus Hagenbuchner, Alessandro Sperduti, Ah Chung Tsoi:
A self-organizing map for adaptive processing of structured data. IEEE Trans. Neural Networks 14(3): 491-505 (2003) - [c32]Pio Nardiello, Fabrizio Sebastiani, Alessandro Sperduti:
Discretizing Continuous Attributes in AdaBoost for Text Categorization. ECIR 2003: 320-334 - [c31]Alessio Micheli, Diego Sona, Alessandro Sperduti:
Formal Determination of Context in Contextual Recursive Cascade Correlation Networks. ICANN 2003: 173-180 - [c30]Fabio Aiolli, Alessandro Sperduti:
Multi-prototype Support Vector Machine. IJCAI 2003: 541-546 - [c29]Alessio Micheli, Filippo Portera, Alessandro Sperduti:
QSAR/QSPR Studies by Kernel Machines, Recursive Neural Networks and Their Integration. WIRN 2003: 308-315 - 2002
- [j16]Fabio Aiolli, Alessandro Sperduti:
A re-weighting strategy for improving margins. Artif. Intell. 137(1-2): 197-216 (2002) - [j15]Paolo Frasconi, Marco Gori, Franz J. Kurfess, Alessandro Sperduti:
Special issue on integration of symbolic and connectionist systems. Cogn. Syst. Res. 3(2): 121-123 (2002) - [j14]Nicola Giusti, Francesco Masulli, Alessandro Sperduti:
Theoretical and Experimental Analysis of a Two-Stage System for Classification. IEEE Trans. Pattern Anal. Mach. Intell. 24(7): 893-904 (2002) - [c28]Francesca Rossi, Alessandro Sperduti, Kristen Brent Venable, Lina Khatib, Paul H. Morris, Robert A. Morris:
Learning and Solving Soft Temporal Constraints: An Experimental Study. CP 2002: 249-263 - [c27]Barbara Hammer, Alessio Micheli, Alessandro Sperduti:
A general framework for unsupervised processing of structured data. ESANN 2002: 389-394 - [c26]Alessandro Sperduti:
On Linear Separability of Sequences and Structures. ICANN 2002: 601-606 - [c25]Fabio Aiolli, Alessandro Sperduti:
An efficient SMO-like algorithm for multiclass SVM. NNSP 2002: 297-306 - 2001
- [j13]Alessio Micheli, Alessandro Sperduti, Antonina Starita, Anna Maria Bianucci:
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. 41(2): 202-218 (2001) - [c24]Alessandro Sperduti:
Neural Networks for Adaptive Processing of Structured Data. ICANN 2001: 5-12 - [c23]Fabio Aiolli, Alessandro Sperduti:
A Simple Additive Re-weighting Strategy for Improving Margins. IJCAI 2001: 927-934 - [c22]Diego Sona, Alessandro Sperduti:
On the Need for a Neural Abstract Machine. Sequence Learning 2001: 135-161 - [c21]Francesca Rossi, Alessandro Sperduti, Lina Khatib, Paul H. Morris, Robert A. Morris:
Learning preferences on temporal constraints: a preliminary report. TIME 2001: 63-68 - [c20]Markus Hagenbuchner, Ah Chung Tsoi, Alessandro Sperduti:
A Supervised Self-Organizing Map for Structured Data. WSOM 2001: 21-28 - [e2]Paolo Frasconi, Marco Gori, Alessandro Sperduti:
Guest Editors' Introduction: Special Section on Connectionist Models for Learning in Structured Domains. IEEE Trans. Knowl. Data Eng. 13(2): 145-147 (2001) - 2000
- [j12]Anna Maria Bianucci, Alessio Micheli, Alessandro Sperduti, Antonina Starita:
Application of Cascade Correlation Networks for Structures to Chemistry. Appl. Intell. 12(1-2): 115-145 (2000) - [j11]Diego Sona, Alessandro Sperduti, Antonina Starita:
Discriminant Pattern Recognition Using Transformation-Invariant Neurons. Neural Comput. 12(6): 1355-1370 (2000) - [c19]Fabrizio Sebastiani, Alessandro Sperduti, Nicola Valdambrini:
An Improved Boosting Algorithm and its Application to Text Categorization. CIKM 2000: 78-85 - [c18]Marco Gori, Paolo Frasconi, Alessandro Sperduti:
Learning Efficiently with Neural Networks: A Theoretical Comparison between Structured and Flat Representations. ECAI 2000: 301-305 - [c17]Alessio Micheli, Diego Sona, Alessandro Sperduti:
Bi-Causal Recurrent Cascade Correlation. IJCNN (3) 2000: 3-8 - [c16]Alessandro Biso, Francesca Rossi, Alessandro Sperduti:
Experimental Results on Learning Soft Constraints. KR 2000: 435-444 - [p1]Antonina Starita, Alessandro Sperduti:
A Neural-Based System for the Automatic Classification and Follow-Up of Diabetic Retinopathies. Artificial Neural Networks in Biomedicine 2000: 233-247
1990 – 1999
- 1999
- [j10]Marco Gori, Andreas Küchler, Alessandro Sperduti:
On the implementation of frontier-to-root tree automata in recursive neural networks. IEEE Trans. Neural Networks 10(6): 1305-1314 (1999) - [c15]Serena La Manna, Anna Maria Colla, Alessandro Sperduti:
Optical Font Recognition for Multi-Font OCR and Document Processing. DEXA Workshop 1999: 549-553 - 1998
- [j9]F. Casalino, Francesco Masulli, Alessandro Sperduti:
Rule Specialization in Networks of Fuzzy Basis Functions. Intell. Autom. Soft Comput. 4(1): 73-81 (1998) - [j8]Francesca Rossi, Alessandro Sperduti:
Learning solution preferences in constraint problems. J. Exp. Theor. Artif. Intell. 10(1): 103-116 (1998) - [j7]Paolo Frasconi, Marco Gori, Alessandro Sperduti:
A general framework for adaptive processing of data structures. IEEE Trans. Neural Networks 9(5): 768-786 (1998) - [c14]Alessandro Biso, Francesca Rossi, Alessandro Sperduti:
Some Experiments on Learning Soft Constraints. CP 1998: 464 - [c13]Paolo Frasconi, Marco Gori, Alessandro Sperduti:
Integration of Graphical Rules with Adaptive Learning of Structured Information. Hybrid Neural Systems 1998: 211-225 - 1997
- [j6]Alessandro Sperduti:
On the Computational Power of Recurrent Neural Networks for Structures. Neural Networks 10(3): 395-400 (1997) - [j5]Alessandro Sperduti, Antonina Starita:
Supervised neural networks for the classification of structures. IEEE Trans. Neural Networks 8(3): 714-735 (1997) - [c12]Enrico Francesconi, Paolo Frasconi, Marco Gori, Simone Marinai, Jianqing Sheng, Giovanni Soda, Alessandro Sperduti:
Logo Recognition by Recursive Neural Networks. GREC 1997: 104-117 - [c11]Nicola Giusti, Alessandro Sperduti, Francesco Masulli:
Competitive and hybrid neuro-fuzzy models for supervised classification. ICNN 1997: 516-521 - [c10]Alessandro Sperduti:
An overview on supervised neural networks for structures. ICNN 1997: 2550-2554 - [c9]Paolo Frasconi, Marco Gori, Alessandro Sperduti:
On the Efficient Classification of Data Structures by Neural Networks. IJCAI 1997: 1066-1071 - [c8]Alessandro Sperduti:
Neural Networks for Processing Data Structures. Summer School on Neural Networks 1997: 121-144 - 1996
- [c7]Alessandro Sperduti, Antonina Starita:
A memory model based on LRAAM for associative access of structures. ICNN 1996: 543-548 - [c6]Diego Sona, Alessandro Sperduti, Antonina Starita:
A Constructive Learning Algorithm for Discriminant Tangent Models. NIPS 1996: 786-792 - [c5]Alessandro Sperduti, Darya Majidi, Antonina Starita:
Extended Cascade-Correlation for Syntactic and Structural Pattern Recognition. SSPR 1996: 90-99 - 1995
- [j4]Alessandro Sperduti:
Book Review: "Neural Network in Computer Intelligence", by LiMin Fu. Int. J. Neural Syst. 6(4): 473-474 (1995) - [j3]Alessandro Sperduti:
Stability properties of labeling recursive auto-associative memory. IEEE Trans. Neural Networks 6(6): 1452-1460 (1995) - [c4]Alessandro Sperduti, Antonina Starita:
Modular Labeling RAAM. ICANNGA 1995: 368-371 - [c3]Alessandro Sperduti, Antonina Starita, Christoph Goller:
Learning Distributed Representations for the Classification of Terms. IJCAI 1995: 509-517 - 1994
- [j2]Alessandro Sperduti:
Labelling Recursive Auto-associative Memory. Connect. Sci. 6(4): 429-459 (1994) - [c2]Alessandro Sperduti, David G. Stork:
A Rapid Graph-based Method for Arbitrary Transformation-Invariant Pattern Classification. NIPS 1994: 665-672 - [e1]Franz J. Kurfess, Alessandro Sperduti:
ICLP 1994 Workshop W3: Logic and Reasoning with Neural Networks, Santa Margherita Ligure, Italy, June 1994. 1994 [contents] - 1993
- [j1]Alessandro Sperduti, Antonina Starita:
Speed up learning and network optimization with extended back propagation. Neural Networks 6(3): 365-383 (1993) - [c1]Alessandro Sperduti:
Encoding Labeled Graphs by Labeling RAAM. NIPS 1993: 1125-1132
Coauthor Index
[j68] [j67] [j66] [j64] [c148] [c146] [c145] [c144] [c140] [c139] [c136] [i26] [j61] [j60] [j59] [j58] [c135] [c134] [c132] [c131] [c130] [c127] [i23] [j54] [j53] [c126] [c124] [c123] [c122] [c121] [c116] [e5] [e4] [i19] [i18] [c114] [c111] [c110] [j51] [j48] [j47] [j46] [c108] [c107] [c106] [i14] [i13] [j44] [c105] [c101] [c98] [i12] [j41] [j40] [c95] [c94] [c92] [c91] [c89] [i9] [i8] [i7] [i6] [i5] [c85] [c79] [c73] [c72]
Dinh Tran-Van
aka: Dinh Van Tran
aka: Dinh Van Tran
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