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* [http://iis-projects.ee.ethz.ch/index.php?title=Exploring_schedules_for_incremental_and_annealing_quantization_algorithms Exploring schedules for incremental and annealing quantization algorithms]
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Revision as of 14:07, 16 November 2020

Matteo Spallanzani

I received my PhD in applied mathematics in February 2020 from the University of Modena and Reggio Emilia (UniMoRe), Italy, with a thesis on "A framework for the analysis of machine learning systems". While at UniMoRe, I have contributed to create the machine learning division of the high-performance real-time (HiPeRT) laboratory led by professor Marko Bertogna. I have been working on data science and machine learning for a while, fields in which I have also had some industrial experiences (Tetra Pak, Maserati).

Interests

I am interested in everything that can help me finding and understanding the patterns hidden in this world. Since I found out that boosting statistical models with parallel computers can be pretty efficient at this, I have made it my job to understand how machine learning systems work, how to combine them and how to apply them to real-world problems. My current research interests lie at the intersection of mathematical analysis, stochastic optimisation and parallel programming. In particular, I am now working on quantized neural networks, applying neural architecture search (NAS) algorithms to improve their topology and function approximation properties, and studying new algorithms to improve their learning process.

Contact Information

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