A survey paper on learning tree distributions through hidden Markov tree models as been accepted for the 2018 FLOC workshop on Learning and Automata (LearnAut’18).
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!
First congratulations to my student Daniele for his first scientific paper:
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!
A paper on generative tree kernels has just been accepted for publication on the prestigious IEEE Transactions on Neural Networks and Learning Systems. Nice Christmas gift for my and my co-authors, Alessio Micheli and Alessandro Sperduti!
Generative Kernels for Tree-Structured Data. In: Neural Networks and Learning Systems, IEEE Transactions on, 2018, ISSN: 2162-2388 .
Today’s presentation day for my paper on deep and wide architecture for tree structured data processing.
Check out the article on Arxiv here.
A paper on randomized neural networks for preference learning with physiological timeseries data has just been accepted for pubblication on the Neurocomputing journal. Congratulations to my Biobeats collaborators!
Randomized neural networks for preference learning with physiological data. In: Neurocomputing, vol. 298, pp. 9-20, 2018.