Category Archives: Students

Accepted papers and sessions at ESANN’19

Good news in the Esann 2019 program!

Congratulations to Francesco Crecchi and Marco Podda for their accepted papers on adversarial attacks and graph generation

Francesco Crecchi, Davide Bacciu, Battista Biggio : Detecting Black-box Adversarial Examples through Nonlinear Dimensionality Reduction. Proceedings of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN'19), i6doc.com, Louvain-la-Neuve, Belgium, 2019.

Davide Bacciu, Alessio Micheli, Marco Podda: Graph generation by sequential edge prediction. Proceedings of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN'19), i6doc.com, Louvain-la-Neuve, Belgium, 2019.

Great success also for the special session on Societal Issues in Machine Learning: When Learning from Data is Not Enough I am co-organizing. We received an high number of great quality papers but only 4 made it to the oral plenary.

New Neurocomputing paper

Congratulations to my student Daniele Castellana for his first journal paper on learning infinite mixture of tree models for structured data clustering. The paper has been selected to be extended for journal publication from the ESANN 2018 best papers.

Bacciu Davide, Castellana Daniele: Bayesian Mixtures of Hidden Tree Markov Models for Structured Data Clustering. In: Neurocomputing, vol. 342, pp. 49-59, 2019, ISBN: 0925-2312.

Deep concentric reservoir paper @IJCNN-WCCI 2018

A paper on a deep concentric reservoir architecture has just been accepted for IJCNN 2018! Congratulations to my student Andrea Bongiorno for his first work!

Now available on Arxiv!

Bacciu Davide, Bongiorno Andrea: Concentric ESN: Assessing the Effect of Modularity in Cycle Reservoirs. Proceedings of the 2018 International Joint Conference on Neural Networks (IJCNN 2018) , IEEE, 2018.

Congratulations to new graduates!

Big day for a hoard of my students graduating today with ML theses!

Antonio Bruno developed a deep learning model for learning tree transductions in the LISTIT project.

Andrea Bongiorno proposes a new deep architecture for reservoirs based on concentric topologies.

Federico Errica discussed (cum Laude!) a new deep generative model for contextual processing of graphs.

Alessio Gravina studied how to help clinicians in early prediction of BPD in low birth-weight infants.

Many congrats as well to Ahmed Alleboudy and Ruben Matino whom I followed in their external theses as UNIPI supervisor.

Good news in ESANN 2018 program

First congratulations to my student Daniele for his first scientific paper:

Bacciu Davide, Castellana Daniele: Mixture of Hidden Markov Models as Tree Encoder. Proceedings of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN'18), i6doc.com, Louvain-la-Neuve, Belgium, 2018, ISBN: 978-287587047-6.

Great success also for the Deep Learning in Bionformatics special session I am co-organizing. We received an high number of great quality papers but only 20% had to be chosen for the oral plenary. Check out the program here!