Giulia Denevi is a PhD student at the Computational Statistics and Machine Learning Department at the Italian Institute of Technology and the Department of Mathematics at the University of Genoa. She received a MSc in Applied Mathematics from the University of Genoa in 2016. Her research interests are in the area of Meta-Learning, Lifelong Learning, Online Learning, Statistical Learning Theory, Optimization and Inverse Problems.
Learning-To-Learn Stochastic Gradient Descent with Biased Regularization. G. Denevi, C. Ciliberto, R. Grazzi, M. Pontil. International Conference on Machine Learning (ICML). Long Beach, California. June 10-15, 2019.
Learning-To-Learn Around A Common Mean. G. Denevi, C. Ciliberto, D. Stamos, M. Pontil. Conference on Neural Information Processing Systems (NeurIPS). Montréal, Canada. December 02-08, 2018.
Incremental Learning-To-Learn with Statistical Guarantees. G. Denevi, C. Ciliberto, D. Stamos, M. Pontil. Conference on Uncertainty in Artificial Intelligence (UAI). Monterey, California. August 06-10, 2018.
Iterative Algorithms For a Non-Linear Inverse Problem in Atmospheric LiDAR. G. Denevi, S. Garbarino, A. Sorrentino. In Inverse Problems, 33, 101239, 2017.