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Predictive Auto-scaling with OpenStack Monasca


Nov 03, 2021
Giacomo Lanciano, Filippo Galli, Tommaso Cucinotta, Davide Bacciu, Andrea Passarella

* Accepted at 2021 IEEE/ACM 14th International Conference on Utility and Cloud Computing (UCC'21) 

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Inductive learning for product assortment graph completion


Oct 04, 2021
Haris Dukic, Georgios Deligiorgis, Pierpaolo Sepe, Davide Bacciu, Marco Trincavelli

* ESANN 2021 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning 
* 6 pages 

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GraphGen-Redux: a Fast and Lightweight Recurrent Model for labeled Graph Generation


Jul 18, 2021
Marco Podda, Davide Bacciu


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TEACHING -- Trustworthy autonomous cyber-physical applications through human-centred intelligence


Jul 14, 2021
Davide Bacciu, Siranush Akarmazyan, Eric Armengaud, Manlio Bacco, George Bravos, Calogero Calandra, Emanuele Carlini, Antonio Carta, Pietro Cassara, Massimo Coppola, Charalampos Davalas, Patrizio Dazzi, Maria Carmela Degennaro, Daniele Di Sarli, Jürgen Dobaj, Claudio Gallicchio, Sylvain Girbal, Alberto Gotta, Riccardo Groppo, Vincenzo Lomonaco, Georg Macher, Daniele Mazzei, Gabriele Mencagli, Dimitrios Michail, Alessio Micheli, Roberta Peroglio, Salvatore Petroni, Rosaria Potenza, Farank Pourdanesh, Christos Sardianos, Konstantinos Tserpes, Fulvio Tagliabò, Jakob Valtl, Iraklis Varlamis, Omar Veledar


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Calliope -- A Polyphonic Music Transformer


Jul 08, 2021
Andrea Valenti, Stefano Berti, Davide Bacciu

* Accepted at ESANN2021 

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Continual Learning with Echo State Networks


May 17, 2021
Andrea Cossu, Davide Bacciu, Antonio Carta, Claudio Gallicchio, Vincenzo Lomonaco

* In review at ESANN 2021 

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A causal learning framework for the analysis and interpretation of COVID-19 clinical data


May 14, 2021
Elisa Ferrari, Luna Gargani, Greta Barbieri, Lorenzo Ghiadoni, Francesco Faita, Davide Bacciu


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Addressing Fairness, Bias and Class Imbalance in Machine Learning: the FBI-loss


May 13, 2021
Elisa Ferrari, Davide Bacciu


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MEG: Generating Molecular Counterfactual Explanations for Deep Graph Networks


Apr 16, 2021
Danilo Numeroso, Davide Bacciu

* 8 pages, 5 figures, to appear in the Proceedings of the 2021 International Joint Conference on Neural Networks (IJCNN 2021) 

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Avalanche: an End-to-End Library for Continual Learning


Apr 01, 2021
Vincenzo Lomonaco, Lorenzo Pellegrini, Andrea Cossu, Antonio Carta, Gabriele Graffieti, Tyler L. Hayes, Matthias De Lange, Marc Masana, Jary Pomponi, Gido van de Ven, Martin Mundt, Qi She, Keiland Cooper, Jeremy Forest, Eden Belouadah, Simone Calderara, German I. Parisi, Fabio Cuzzolin, Andreas Tolias, Simone Scardapane, Luca Antiga, Subutai Amhad, Adrian Popescu, Christopher Kanan, Joost van de Weijer, Tinne Tuytelaars, Davide Bacciu, Davide Maltoni

* Official Website: https://avalanche.continualai.org 

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Distilled Replay: Overcoming Forgetting through Synthetic Samples


Mar 29, 2021
Andrea Rosasco, Antonio Carta, Andrea Cossu, Vincenzo Lomonaco, Davide Bacciu


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Continual Learning for Recurrent Neural Networks: an Empirical Evaluation


Mar 24, 2021
Andrea Cossu, Antonio Carta, Vincenzo Lomonaco, Davide Bacciu

* In submission 

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Catastrophic Forgetting in Deep Graph Networks: an Introductory Benchmark for Graph Classification


Mar 22, 2021
Antonio Carta, Andrea Cossu, Federico Errica, Davide Bacciu

* Accepted at the 2021 Web Conference Workshop on Graph Learning Benchmarks (GLB 2021). Code available at https://github.com/diningphil/continual_learning_for_graphs 

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Continual Learning for Recurrent Neural Networks: a Review and Empirical Evaluation


Mar 12, 2021
Andrea Cossu, Antonio Carta, Vincenzo Lomonaco, Davide Bacciu

* In submission 

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Graph Mixture Density Networks


Dec 05, 2020
Federico Errica, Davide Bacciu, Alessio Micheli


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Explaining Deep Graph Networks with Molecular Counterfactuals


Nov 09, 2020
Danilo Numeroso, Davide Bacciu

* 6 pages, 6 figures, accepted at NeurIPS2020 Workshop on Machine Learning for Molecules 

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


Nov 05, 2020
Antonio Carta, Alessandro Sperduti, Davide Bacciu

* Accepted at NeurIPS 2020 workshop "Beyond Backpropagation: Novel Ideas for Training Neural Architectures" 

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Learning from Non-Binary Constituency Trees via Tensor Decomposition


Nov 02, 2020
Daniele Castellana, Davide Bacciu

* Accepted at COLING2020 

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Generative Tomography Reconstruction


Oct 26, 2020
Matteo Ronchetti, Davide Bacciu

* Accepted as a poster for the NeurIPS 2020 Workshop on Deep Learning and Inverse Problems 

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FADER: Fast Adversarial Example Rejection


Oct 18, 2020
Francesco Crecchi, Marco Melis, Angelo Sotgiu, Davide Bacciu, Battista Biggio

* Submitted as a Neurocomputing journal paper 

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Perplexity-free Parametric t-SNE


Oct 03, 2020
Francesco Crecchi, Cyril de Bodt, Michel Verleysen, John A. Lee, Davide Bacciu

* ESANN 2020 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Online event, 2-4 October 2020, i6doc.com publ., ISBN 978-2-87587-074-2. Available from http://www.i6doc.com/en/ 

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ROS-Neuro Integration of Deep Convolutional Autoencoders for EEG Signal Compression in Real-time BCIs


Aug 31, 2020
Andrea Valenti, Michele Barsotti, Raffaello Brondi, Davide Bacciu, Luca Ascari

* Accepted at the IEEE International Conference on Systems, Man, and Cybernetics (SMC 2020) 

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Accelerating the identification of informative reduced representations of proteins with deep learning for graphs


Jul 14, 2020
Federico Errica, Marco Giulini, Davide Bacciu, Roberto Menichetti, Alessio Micheli, Raffaello Potestio


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Incremental Training of a Recurrent Neural Network Exploiting a Multi-Scale Dynamic Memory


Jun 29, 2020
Antonio Carta, Alessandro Sperduti, Davide Bacciu

* accepted @ ECML 2020. arXiv admin note: substantial text overlap with arXiv:2001.11771 

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Tensor Decompositions in Recursive NeuralNetworks for Tree-Structured Data


Jun 18, 2020
Daniele Castellana, Davide Bacciu

* Accepted at ESANN2020 

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Generalising Recursive Neural Models by Tensor Decomposition


Jun 17, 2020
Daniele Castellana, Davide Bacciu

* Accepted at IEEE WCCI2020 

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Continual Learning with Gated Incremental Memories for sequential data processing


Apr 08, 2020
Andrea Cossu, Antonio Carta, Davide Bacciu

* Accepted as a conference paper at 2020 International Joint Conference on Neural Networks (IJCNN 2020). Part of 2020 IEEE World Congress on Computational Intelligence (IEEE WCCI 2020) 

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A Deep Generative Model for Fragment-Based Molecule Generation


Feb 28, 2020
Marco Podda, Davide Bacciu, Alessio Micheli


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Tensor Decompositions in Deep Learning


Feb 26, 2020
Davide Bacciu, Danilo P. Mandic


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Learning Style-Aware Symbolic Music Representations by Adversarial Autoencoders


Feb 20, 2020
Andrea Valenti, Antonio Carta, Davide Bacciu

* Accepted for publication at the 24th European Conference on Artificial Intelligence (ECAI2020) 

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