Alessandro Epasto
I am a staff research scientist at Google, New York working in the Algorithms and Optimization team lead by Vahab Mirrokni.
I received a Ph.D in computer science from Sapienza University of Rome, where I was advised by Professor Alessandro Panconesi and supported by the Google Europe Ph.D. Fellowship in Algorithms, 2011.
I was also a post-doc at the department of computer science of Brown University in Providence (RI), USA where I was advised by Professor Eli Upfal.
My research interests include algorithmic problems in machine learning and data mining, in particular in the areas of clustering, privacy and large scale graphs analysis.
Authored Publications
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Measuring Re-identification Risk
Travis Dick
Adel Javanmard
Josh Karlin
Gabriel Henrique Nunes
SIGMOD (2023)
Private estimation algorithms for stochastic block models and mixture models
Hongjie Chen
Tommaso D'Orsi
Jacob Imola
David Steurer
Stefan Tiegel
54rd Annual ACM Symposium on Theory of Computing (STOC'23) (2023)
Scalable Differentially Private Clustering via Hierarchically Separated Trees
Chris Schwiegelshohn
David Saulpic
2022 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (2022) (to appear)
Differentially Private Graph Learning via Sensitivity-Bounded Personalized PageRank
Advances in Neural Information Processing Systems (2022)
Near-Optimal Private and Scalable k-Clustering
Shyam Narayanan
NeurIPS 2022 (2022)
Fair Hierarchical Clustering
Benjamin Moseley
Marina Knittel
Yuyan Wang
Neurips 2020
Bisect and Conquer: Hierarchical Clustering via Max-Uncut Bisection
Vaggos Chatziafratis
AISTATS, AISTATS, AISTATS (2020), AISTATS (to appear)
Fair Correlation clustering
23rd International Conference on Artificial Intelligence and Statistics (AISTATS 2020) (2020) (to appear)
Sliding Window Algorithms for k-Clustering Problems
Michele Borassi
Neurips 2020 (to appear)
