- Postdoc SpeechTek (ST)
Alessandro Rossi obtained is M. Sc. in Mathematics in 2013 at University of Siena.
In 2017 he completed is Ph.D. in Computing Systems at Department of Information Engineering and Mathematics of University of Siena, investigating the inclusion of Temporal Coherence constraints in Regularization Methods for Machine Learning optimization algortihms.
From 2017 to 2018 he had a scholarship at the Department of Social, Political and Cognitive Sciences of the University of Siena, working on Novelty Detection applications for Audio and Video Surveillance and for Industrial Systems Monitoring, collaborating with the UDOO Team.
Since May 2018 is a fixed-term post-doc researcher at FBK working on Deep Learning methods for Speaker Diarization applications.
- Gori M., Maggini M., Rossi A.: Neural Network Training as a Dissipative Process, Neural Networks, 81, 72-80, 2016
- Rossi A., Rizzo A., Montefoschi F.: ATM Protection Using Embedeed Deep Learning solutions. IAPR Workshop on Artificial Neural Networks in Pattern Recognition, 371-382, 2018
- Rossi A. et al.: Auto-Associative Recurrent Neural Networks and Long Term Dependencies in Novelty Detection for Audio Surveillance Applications, IOP Conference Series: Materials Science and Engineering, Vol. 261–1, 2017
- Maggini M., Rossi A.: On-line Learning on Temporal Manifolds, 15th International Conference of the Italian Association for Artificial Intelligence – AI*IA, 321-333, 2016
- Giannini F., Laveglia V., Rossi A., Zanca D., Zugarini A.: Neural Networks for Beginners. A fast implementation in Matlab, Torch, Tensorflow, arXiv preprint arXiv:1703.05298, 2017
- Gori M.,Maggini M., Rossi A.: The principle of cognitive action-preliminary experimental analysis, arXiv preprint arXiv:1701.02377, 2017
- Gori M.,Maggini M., Rossi A.: Collapsing of dimensionality, arXiv preprint arXiv:1701.00831, 2017