Congratulations to Francesco Crecchi that just defended his Ph.D. thesis on “Deep Learning Safety under Non-Stationarity Assumptions”, jointly supervised by me and Battista Biggio. Francesco is my first Ph.D. student to graduate, so that doubles the celebrations on my side. …
The new edition of the Reinforcement Learning course will kickoff on Monday 29/03/2021 h. 16.00. This is a course offered to M.Sc. Students of the AI Curriculum (recognition as 3 Free-choice CFU) and Ph.D. students. For furher information please check …
Excellent result by our group in the upcoming NeurIPS 2020 workshops with four accepted papers.Congrats to Antonio Carta, Francesco Landolfi, Danilo Numeroso and Matteo Ronchetti! Preprints coming up..
Couldn’t think of a better venue for my 99th research paper than the Journal of Machine Learning Research. Check out our work on deep and probabilistic learning for graphs. Terrific job by Federico Errica!
Congratulations to Alessio Gravina, for his joint Stanford-UNIPI thesis on deep learning for graphs hitting the news: https://www.unipi.it/index.php/news/item/17721-tesi-congiunta-con-stanford-per-un-giovane-laureato-in-informatica
While classes are suspended, University is still open and today we had a great (epidemiologically-correct) graduation day with 5 of my students having discussed their B.Sc. and M.Sc. theses. Great works on graph neural networks applied to biochemistry and social-network …
Many congratulations to Francesca Lizzi for winning the best Ph.D. project award at BIOSTEC 2020 with her thesis project on “Deep-learning based analysis of mammograms to improve the estimation of breast cancer risk”. Terrific job!
The 2019/20 edition of the ISPR course will start with the first lecture on THURSDAY 20 FEBRUARY 2020 – h. 14-16 CLASSROOM L1 – POLO FIBONACCI (First Floor) See you there!
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!
Thanks to the invaluable work of my student Valerio De Caro, the code for the Hidden Tree Markov Network has been finally released. Check out Valerio’s github.