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Sitemap
A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
About me
About me
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Posts
portfolio
Data Science base image
Base Docker image for CI/CD Data Science workflows.
Machine Learning pipelines on Google Cloud Platform (GCP)
A collection of reusable templates for training and deploying ML models on GCP Vertex AI.
Meat Quality Assessment using Deep Neural Networks
Deep Learning model to assess the quality of red meat based on sample photos.
publications
Distributed music classification using Random Vector Functional-Link nets
S. Scardapane, R. Fierimonte, D. Wang, M. Panella, and A. Uncini, "Distributed music classification using Random Vector Functional-Link nets," 2015 International Joint Conference on Neural Networks (IJCNN), Killarney, Ireland, 2015, pp. 1-8, doi: 10.1109/IJCNN.2015.7280333.
Distributed learning of Random Weights Fuzzy Neural Networks
R. Fierimonte, M. Barbato, A. Rosato, and M. Panella, "Distributed learning of Random Weights Fuzzy Neural Networks," 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Vancouver, BC, Canada, 2016, pp. 2287-2294, doi: 10.1109/FUZZ-IEEE.2016.7737978.
Distributed semi-supervised support vector machines
S. Scardapane, R. Fierimonte, P. Di Lorenzo, M. Panella, and A. Uncini. "Distributed Semi-Supervised Support Vector Machines", in Neural Networks, vol. 80, pp. 43-52, Elsevier, 2016, doi: 10.1016/j.neunet.2016.04.007.
Fully Decentralized Semi-supervised Learning via Privacy-preserving Matrix Completion
R. Fierimonte, S. Scardapane, A. Uncini, and M. Panella, "Fully Decentralized Semi-supervised Learning via Privacy-preserving Matrix Completion," in IEEE Transactions on Neural Networks and Learning Systems, vol. 28, no. 11, pp. 2699-2711, Nov. 2017, doi: 10.1109/TNNLS.2016.2597444.
Improving latent variable descriptiveness by modelling rather than ad-hoc factors
A. Mansbridge, R. Fierimonte, I. Feige, and D. Barber, "Improving latent variable descriptiveness by modelling rather than ad-hoc factors", in Machine Learning, vol. 108, pp. 1601–1611, 2019, doi: 10.1007/s10994-019-05830-1.
talks
Talk 1 on Relevant Topic in Your Field
This is a description of your talk, which is a markdown files that can be all markdown-ified like any other post. Yay markdown!
Conference Proceeding talk 3 on Relevant Topic in Your Field
This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.