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Massimiliano Pontil

Senior Researcher Tenured - Principal Investigator
Computational Statistics and Machine Learning
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About

Massimiliano Pontil received an MSc degree in Physics from the University of Genova in 1994 (summa cum laude) and a PhD in Physics from the same University in 1999. His main research interests are in machine learning, function representation and approximation, numerical optimization, regularization methods, and statistical learning theory. He has made contributions in the areas including kernel methods, multitask and transfer learning, online learning, sparsity regularization, and statistical learning theory. He also studied machine learning applications arising in affective computing, bioinformatics, computer vision, and user modelling, among others. He has published over 30 international journals papers, 10 book chapters and 60 peer reviewed conference proceedings. His research papers have been cited approximately 12,000 times and his h-index is 47 (Google Scholar, March 2016). He was a full time member of academic staff at University College London (UCL) between 2003 and 2015, a Research Associate in the Department of Information Engineering at University of Siena (2001--2002) and a Post-doctoral Fellow at the Massachusetts Institute of Technology (1998--2000). He has been on the programme committee of the main machine learning conferences, including the Annual Conference on Learning Theory (COLT), the International Conference on Machine Learning (ICML), and the Annual Conference on Neural Information Processing Systems (NIPS). He is on the editorial board of the Machine Learning Journal, Statistics and Computing, the Journal of Machine Learning Research, and he is on the Scientific Advisory Board of the Max Planck Institute for Intelligent Systems.

Education

Title: Ph.D. in Physics
Institute: University of Genoa
Location: Genoa
Country: Italy
From: 1996 To: 1999

All Publications
2021
Pasteris S., Herbster M., Vitale F., Pontil M.
A Gang of Adversarial Bandits
Advances in Neural Information Processing Systems 35 (NeurIPS 2021)
Conference Paper Conference
2021
Cella L., Pontil M., Gentile C.
Best Model Identification: A Rested Bandit Formulation
International Conference on Machine Learning, vol. 139, pp. 1362-1372
Conference Paper Conference
2021
Maurer M., Pontil M.
Concentration inequalities under sub-Gaussian and sub-exponential conditions
Advances in Neural Information Processing Systems 35 (NeurIPS 2021)
Conference Paper Conference
2021
Grazzi R., Salzo S., Pontil M.
Convergence Properties of Stochastic Hypergradients
The 24th International Conference on Artificial Intelligence and Statistics
Article Conference
2021
Gouk H., Hospedales T. M., Pontil M.
Distance-Based Regularisation of Deep Networks for Fine-Tuning
International Conference on Learning Representations
Conference Paper Conference