Category Archives: news

New accepted papers

A bunch of new papers on deep learning for graphs and neural language processing has just been accepted for publication. Check them out!

Davide Bacciu, Antonio Carta: Sequential Sentence Embeddings for Semantic Similarity. Proceedings of the 2019 IEEE Symposium Series on Computational Intelligence (SSCI'19), IEEE, 2019.

Michele Cafagna, Lorenzo De Mattei, Davide Bacciu, Malvina Nissim: Suitable doesn’t mean attractive. Human-based evaluation of automatically generated headlines. Proceedings of the 6th Italian Conference on Computational Linguistics (CLiC-it 2019), vol. 2481 , AI*IA series CEUR, 2019.

Davide Bacciu, Luigi Di Sotto: A non-negative factorization approach to node pooling in graph convolutional neural networks. Proceedings of the 18th International Conference of the Italian Association for Artificial Intelligence (AIIA 2019), Lecture Notes in Artificial Intelligence Springer-Verlag, 2019.

Special session on tensor methods for deep learning @ESANN2020

I am co-organizing with Danilo Mandic a special session on “Tensor Decompositions in Deep Learning” at ESANN 2020.

We welcome solid contributions and preliminary relevant results showing potential, limitations and challenges of new ideas related to the use of tensor decompositions in deep learning, neural networks, and machine learning at large.

Deadline for paper submission: 18 November 2019.

Prospective contributors/participants can contact me (or another co-organizer) for details.

Organized by Davide Bacciu (University of Pisa,Italy), Danilo Mandic (Imperial College, UK).

New Graduates

Congratulations to Luigi di Sotto and Stefan Daniel Motoc for having completed their M.Sc. and B.Sc. in Computer Science with a final project on deep learning topics. Luigi discussed a novel pooling mechanism for graph convolutional networks. Stefan proposed a thorough analysis of the latent space of MusAE, our deep adversarial autoencoder for music generation.

Paper accepted @IJCNN 2019

A paper on Bayesian tensor factorization for efficient processing of structured data has just been accepted for IJCNN 2019. Check it out:

Daniele Castellana, Davide Bacciu: Bayesian Tensor Factorisation for Bottom-up Hidden Tree Markov Models. Proceedings of the 2019 International Joint Conference on Neural Networks (IJCNN 2019I) , IEEE, 2019.

New ML graduates

Congratulations to two of my students who succesfully defended their B.Sc. and M.Sc. theses with two excellent ML projects.

Lorenzo Marsicano developed microESN, a library for the development of recurrent neural networks in embedded systems with minimal memory and computational resources.

Andrea Valenti designed a new deep learning model for MIDI music generation, beautifully named MusAE, for Music Adversarial autoEncoder (and of course to honour Greek mythology).

Congratulations!!