Hidden tree Markov models in Python
Thanks to my student Federico Errica, it is now available the official Python release for the Bottom-up Hidden Tree Markov model. The Python code for the model can be downloaded on Federico’s Github.
Month: November 2017
New journal paper accepted
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!
Organizing a Deep Learning Special Session @WCCI2018
New upocoming special session: I am co-organizing a Deep Learning for Structured and Multimedia Information (DEEPSM) session at WCCI2018. The session is meant to attract researchers working on the next generation of deep learning models for machine vision and multimedia …
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New Ph.D. Students
Welcome to four new Ph.D. students joining the Machine Learning group under my supervision: Antonio Carta, Daniele Castellana, Francesco Crecchi and Marco Podda. Looking forward to be working with you guys!