Category Archives: machine learning

COVID-19 Task Force

If you work in AI and you are willing to contribute to the worldwide fight against COVID-19 please consider joining the CLAIRE-COVID19 task force. I am coordinating the workgroup on omics, chemical and clinical data processing.

You can have a look at the first result of our pan-european collaboration which has been released here: it is a curated repository of protein-viral-drug-disease interactions for helping research in drug repurposing, bio-informatics, etc.

Big @ESANN2020

Great success at ESANN this year, with 5 papers in: congrats to Daniele, Francesco, Federico and Marco!!

Marco Podda, Alessio Micheli, Davide Bacciu, Paolo Milazzo: Biochemical Pathway Robustness Prediction with Graph Neural Networks . Proceedings of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN'20), 2020.
Federico Errica, Davide Bacciu, Alessio Micheli: Theoretically Expressive and Edge-aware Graph Learning . Proceedings of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN'20), 2020.
Francesco Crecchi, Cyril de Bodt, Davide Bacciu, Michel Verleysen, Lee John: Perplexity-free Parametric t-SNE. Proceedings of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN'20), 2020.
Davide Bacciu, Danilo Mandic: Tensor Decompositions in Deep Learning. Proceedings of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN'20), 2020.
Daniele Castellana, Davide Bacciu: Tensor Decompositions in Recursive Neural Networks for Tree-Structured Data . Proceedings of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN'20), 2020.

Artificial Intelligence in Medicine paper

Check out our newly accepted journal paper on discovering and measuring the confounding effect of data attributes in biomedical tasks. Preprint available on the Arvix. Congratulations to Elisa!

Elisa Ferrari, Alessandra Retico, Davide Bacciu: Measuring the effects of confounders in medical supervised classification problems: the Confounding Index (CI). In: Artificial Intelligence in Medicine, vol. 103, 2020.

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 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!!

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.

Learning on Graphs and Explainable ML sessions @IJCNN 2019

I am co-organizing two special sessions at IJCNN 2019 next summer:

  • Special Session on Explainable Machine Learning, organized by Davide Bacciu (University of Pisa), Paulo J.G. Lisboa (Liverpool John Moores University), José D. Martín-Guerrero (Universitat de Valencia), Alfredo Vellido (Universitat Politècnica de Catalunya)
  • Special Session on Learning Representations for Structured Data, organized by Davide Bacciu (University of Pisa), Thomas Gärtner (University of Nottingham), Nicolò Navarin (University of Padova) and Alessandro Sperduti (University of Padova)

Paper submission deadline is 15 December 2018 (extension pending).

Send you work through the conference submission site!

Special session on societal issues in machine learning @ESANN2019

I am co-organizing a special session at the upcoming ESANN 2019 on societal impacts of artificial intelligence, covering privacy, safety, ethical and fairness issues of machine learning.

We welcome contributions both from a theoretical and methodological side, as well as studies stemming from major research initiatives and projects focusing on the session topics.

Deadline for paper submission: 19 November 2018.

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

Organized by Davide Bacciu (University of Pisa,Italy), Battista Biggio (University of Cagliari, Italy), Paulo J. G. Lisboa, (Liverpool John Moores University, U.K.), José D. Martín (Universitat de València, Spain), Luca Oneto (University of Genoa, Italy), Alfredo Vellido (Universitat Politècnica de Catalunya, Spain)