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ORCIDAlessandro Sperduti
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- affiliation: University of Padua, Italy
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2020 – today
- 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) - [c151]Flavio Petruzzellis, Alberto Testolin, Alessandro Sperduti:
Benchmarking GPT-4 on Algorithmic Problems: A Systematic Evaluation of Prompting Strategies. LREC/COLING 2024: 2161-2177 - [c150]Muhammad Uzair-Ul-Haq, Davide Rigoni, Alessandro Sperduti:
Prompt-Based Data Augmentation Using Contrastive Learning Under Scarcity of Annotated Data. ECAI 2024: 2717-2724 - [c149]Samuel Cognolato, Alessandro Sperduti, Luciano Serafini:
IFH: A Diffusion Framework for Flexible Design of Graph Generative Models. ECAI 2024: 3039-3046 - [c148]Flavio Petruzzellis, Alberto Testolin, Alessandro Sperduti:
A Neural Rewriting System to Solve Algorithmic Problems. ECAI 2024: 3112-3119 - [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]