Alessandro Epasto

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 58

Top Topics

Differentially Private

Top Venues

Publications

Alessandro Epasto, Hossein Esfandiari, Vahab Mirrokni, Andrés Muñoz Medina
Smooth Anonymity for Sparse Graphs. WWW (Companion Volume) (2024)
Rudrajit Das, Inderjit S. Dhillon, Alessandro Epasto, Adel Javanmard, Jieming Mao, Vahab Mirrokni, Sujay Sanghavi, Peilin Zhong
Retraining with Predicted Hard Labels Provably Increases Model Accuracy. CoRR (2024)
MohammadHossein Bateni, Vincent Cohen-Addad, Alessandro Epasto, Silvio Lattanzi
A Scalable Algorithm for Individually Fair k-Means Clustering. AISTATS (2024)
Vincent Cohen-Addad, Tommaso d'Orsi, Alessandro Epasto, Vahab Mirrokni, Peilin Zhong
Perturb-and-Project: Differentially Private Similarities and Marginals. CoRR (2024)
Alessandro Epasto, Quanquan C. Liu, Tamalika Mukherjee, Felix Zhou
The Power of Graph Sparsification in the Continual Release Model. CoRR (2024)
MohammadHossein Bateni, Vincent Cohen-Addad, Alessandro Epasto, Silvio Lattanzi
A Scalable Algorithm for Individually Fair K-means Clustering. CoRR (2024)
Alessandro Epasto, Jieming Mao, Andres Muñoz Medina, Vahab Mirrokni, Sergei Vassilvitskii, Peilin Zhong
Differentially Private Continual Releases of Streaming Frequency Moment Estimations. CoRR (2023)
Jacob Imola, Alessandro Epasto, Mohammad Mahdian, Vincent Cohen-Addad, Vahab Mirrokni
Differentially-Private Hierarchical Clustering with Provable Approximation Guarantees. CoRR (2023)
CJ Carey, Travis Dick, Alessandro Epasto, Adel Javanmard, Josh Karlin, Shankar Kumar, Andres Muñoz Medina, Vahab Mirrokni, Gabriel Henrique Nunes, Sergei Vassilvitskii, Peilin Zhong
Measuring Re-identification Risk. Proc. ACM Manag. Data 1 (2) (2023)
Jacob Imola, Alessandro Epasto, Mohammad Mahdian, Vincent Cohen-Addad, Vahab Mirrokni
Differentially Private Hierarchical Clustering with Provable Approximation Guarantees. ICML (2023)
Alessandro Epasto, Tamalika Mukherjee, Peilin Zhong
Differentially Private Clustering in Data Streams. CoRR (2023)
CJ Carey, Travis Dick, Alessandro Epasto, Adel Javanmard, Josh Karlin, Shankar Kumar, Andrés Muñoz Medina, Vahab Mirrokni, Gabriel Henrique Nunes, Sergei Vassilvitskii, Peilin Zhong
Measuring Re-identification Risk. CoRR (2023)
Hongjie Chen, Vincent Cohen-Addad, Tommaso d'Orsi, Alessandro Epasto, Jacob Imola, David Steurer, Stefan Tiegel
Private estimation algorithms for stochastic block models and mixture models. NeurIPS (2023)
Hongjie Chen, Vincent Cohen-Addad, Tommaso d'Orsi, Alessandro Epasto, Jacob Imola, David Steurer, Stefan Tiegel
Private estimation algorithms for stochastic block models and mixture models. CoRR (2023)
Alessandro Epasto, Jieming Mao, Andres Muñoz Medina, Vahab Mirrokni, Sergei Vassilvitskii, Peilin Zhong
Differentially Private Continual Releases of Streaming Frequency Moment Estimations. ITCS (2023)
Alessandro Epasto, Vahab Mirrokni, Shyam Narayanan, Peilin Zhong
k-Means Clustering with Distance-Based Privacy. NeurIPS (2023)
Alessandro Epasto, Vahab Mirrokni, Bryan Perozzi, Anton Tsitsulin, Peilin Zhong
Differentially Private Graph Learning via Sensitivity-Bounded Personalized PageRank. CoRR (2022)
Vincent Cohen-Addad, Alessandro Epasto, Silvio Lattanzi, Vahab S. Mirrokni, Andres Munoz, David Saulpic, Chris Schwiegelshohn, Sergei Vassilvitskii
Scalable Differentially Private Clustering via Hierarchically Separated Trees. CoRR (2022)
Vincent Cohen-Addad, Alessandro Epasto, Silvio Lattanzi, Vahab Mirrokni, Andres Muñoz Medina, David Saulpic, Chris Schwiegelshohn, Sergei Vassilvitskii
Scalable Differentially Private Clustering via Hierarchically Separated Trees. KDD (2022)
Alessandro Epasto, Mohammad Mahdian, Vahab S. Mirrokni, Peilin Zhong
Massively Parallel and Dynamic Algorithms for Minimum Size Clustering. SODA (2022)
Matteo Almanza, Alessandro Epasto, Alessandro Panconesi, Giuseppe Re
k-Clustering with Fair Outliers. WSDM (2022)
Hossein Esfandiari, Alessandro Epasto, Vahab S. Mirrokni, Andres Muñoz Medina, Sergei Vassilvitskii
Smooth Anonymity for Sparse Binary Matrices. CoRR (2022)
Alessandro Epasto, Mohammad Mahdian, Vahab S. Mirrokni, Peilin Zhong
Improved Sliding Window Algorithms for Clustering and Coverage via Bucketing-Based Sketches. SODA (2022)
Alessandro Epasto, Vahab Mirrokni, Bryan Perozzi, Anton Tsitsulin, Peilin Zhong
Differentially Private Graph Learning via Sensitivity-Bounded Personalized PageRank. NeurIPS (2022)
Vincent Cohen-Addad, Alessandro Epasto, Vahab Mirrokni, Shyam Narayanan, Peilin Zhong
Near-Optimal Private and Scalable $k$-Clustering. NeurIPS (2022)
Alessandro Epasto, Andrés Muñoz Medina, Steven Avery, Yijian Bai, Róbert Busa-Fekete, C. J. Carey, Ya Gao, David Guthrie, Subham Ghosh, James Ioannidis, Junyi Jiao, Jakub Lacki, Jason Lee, Arne Mauser, Brian Milch, Vahab S. Mirrokni, Deepak Ravichandran, Wei Shi, Max Spero, Yunting Sun, Umar Syed, Sergei Vassilvitskii, Shuo Wang
Clustering for Private Interest-based Advertising. KDD (2021)
Alessandro Epasto, Mohammad Mahdian, Vahab S. Mirrokni, Peilin Zhong
Massively Parallel and Dynamic Algorithms for Minimum Size Clustering. CoRR (2021)
Alessandro Epasto, Mohammad Mahdian, Vahab S. Mirrokni, Peilin Zhong
Improved Sliding Window Algorithms for Clustering and Coverage via Bucketing-Based Sketches. CoRR (2021)
Sara Ahmadian, Alessandro Epasto, Ravi Kumar, Mohammad Mahdian
Fair Correlation Clustering. CoRR (2020)
Sara Ahmadian, Alessandro Epasto, Marina Knittel, Ravi Kumar, Mohammad Mahdian, Benjamin Moseley, Philip Pham, Sergei Vassilvitskii, Yuyan Wang
Fair Hierarchical Clustering. NeurIPS (2020)
Sara Ahmadian, Alessandro Epasto, Marina Knittel, Ravi Kumar, Mohammad Mahdian, Benjamin Moseley, Philip Pham, Sergei Vassilvitskii, Yuyan Wang
Fair Hierarchical Clustering. CoRR (2020)
Alessandro Epasto, Mohammad Mahdian, Vahab S. Mirrokni, Manolis Zampetakis
Optimal Approximation - Smoothness Tradeoffs for Soft-Max Functions. CoRR (2020)
Vaggos Chatziafratis, Grigory Yaroslavtsev, Euiwoong Lee, Konstantin Makarychev, Sara Ahmadian, Alessandro Epasto, Mohammad Mahdian
Bisect and Conquer: Hierarchical Clustering via Max-Uncut Bisection. AISTATS (2020)
Alessandro Epasto, Mohammad Mahdian, Vahab S. Mirrokni, Emmanouil Zampetakis
Optimal Approximation - Smoothness Tradeoffs for Soft-Max Functions. NeurIPS (2020)
Michele Borassi, Alessandro Epasto, Silvio Lattanzi, Sergei Vassilvitskii, Morteza Zadimoghaddam
Sliding Window Algorithms for k-Clustering Problems. CoRR (2020)
Michele Borassi, Alessandro Epasto, Silvio Lattanzi, Sergei Vassilvitskii, Morteza Zadimoghaddam
Sliding Window Algorithms for k-Clustering Problems. NeurIPS (2020)
Alessandro Epasto, Mohammad Mahdian, Jieming Mao, Vahab S. Mirrokni, Lijie Ren
Smoothly Bounding User Contributions in Differential Privacy. NeurIPS (2020)
Sara Ahmadian, Alessandro Epasto, Ravi Kumar, Mohammad Mahdian
Fair Correlation Clustering. AISTATS (2020)
Alessandro Epasto, Bryan Perozzi
Is a Single Embedding Enough? Learning Node Representations that Capture Multiple Social Contexts. WWW (2019)
Alessandro Epasto, Vahab S. Mirrokni, Morteza Zadimoghaddam
Scalable Diversity Maximization via Small-size Composable Core-sets (Brief Announcement). SPAA (2019)
Sara Ahmadian, Vaggos Chatziafratis, Alessandro Epasto, Euiwoong Lee, Mohammad Mahdian, Konstantin Makarychev, Grigory Yaroslavtsev
Bisect and Conquer: Hierarchical Clustering via Max-Uncut Bisection. CoRR (2019)
Sara Ahmadian, Alessandro Epasto, Ravi Kumar, Mohammad Mahdian
Clustering without Over-Representation. CoRR (2019)
Alessandro Epasto, Bryan Perozzi
Is a Single Embedding Enough? Learning Node Representations that Capture Multiple Social Contexts. CoRR (2019)
Sara Ahmadian, Alessandro Epasto, Ravi Kumar, Mohammad Mahdian
Clustering without Over-Representation. KDD (2019)
Michele Borassi, Alessandro Epasto, Silvio Lattanzi, Sergei Vassilvitskii, Morteza Zadimoghaddam
Better Sliding Window Algorithms to Maximize Subadditive and Diversity Objectives. PODS (2019)
Alessandro Epasto, Hossein Esfandiari, Vahab S. Mirrokni
On-Device Algorithms for Public-Private Data with Absolute Privacy. WWW (2019)
Alessandro Epasto, Eli Upfal
Efficient Approximation for Restricted Biclique Cover Problems. Algorithms 11 (6) (2018)
Alessandro Epasto, Mohammad Mahdian, Vahab S. Mirrokni, Song Zuo
Incentive-Aware Learning for Large Markets. WWW (2018)
Lorenzo De Stefani, Alessandro Epasto, Matteo Riondato, Eli Upfal
TRIÈST: Counting Local and Global Triangles in Fully Dynamic Streams with Fixed Memory Size. ACM Trans. Knowl. Discov. Data 11 (4) (2017)
Alessandro Epasto, Silvio Lattanzi, Renato Paes Leme
Ego-Splitting Framework: from Non-Overlapping to Overlapping Clusters. KDD (2017)
Alessandro Epasto, Silvio Lattanzi, Sergei Vassilvitskii, Morteza Zadimoghaddam
Submodular Optimization Over Sliding Windows. WWW (2017)
Alessandro Epasto, Vahab S. Mirrokni, Morteza Zadimoghaddam
Bicriteria Distributed Submodular Maximization in a Few Rounds. SPAA (2017)
Alessandro Epasto, Ahmad Mahmoody, Eli Upfal
Real-Time Targeted-Influence Queries over Large Graphs. ASONAM (2017)
David Stück, Haraldur Tómas Hallgrímsson, Greg Ver Steeg, Alessandro Epasto, Luca Foschini
The Spread of Physical Activity Through Social Networks. WWW (2017)
Lorenzo De Stefani, Alessandro Epasto, Matteo Riondato, Eli Upfal
TRIÈST: Counting Local and Global Triangles in Fully-dynamic Streams with Fixed Memory Size. CoRR (2016)
Lorenzo De Stefani, Alessandro Epasto, Matteo Riondato, Eli Upfal
TRIÈST: Counting Local and Global Triangles in Fully-Dynamic Streams with Fixed Memory Size. KDD (2016)
Lorenzo De Stefani, Alessandro Epasto, Eli Upfal, Fabio Vandin
Reconstructing Hidden Permutations Using the Average-Precision (AP) Correlation Statistic. AAAI (2016)
Alessandro Epasto, Silvio Lattanzi, Sergei Vassilvitskii, Morteza Zadimoghaddam
Submodular Optimization over Sliding Windows. CoRR (2016)
Alessandro Epasto, Silvio Lattanzi, Vahab S. Mirrokni, Ismail Sebe, Ahmed Taei, Sunita Verma
Ego-net Community Mining Applied to Friend Suggestion. Proc. VLDB Endow. 9 (4) (2015)
Alessandro Epasto, Silvio Lattanzi, Mauro Sozio
Efficient Densest Subgraph Computation in Evolving Graphs. WWW (2015)
Flavio Chierichetti, Alessandro Epasto, Ravi Kumar, Silvio Lattanzi, Vahab S. Mirrokni
Efficient Algorithms for Public-Private Social Networks. KDD (2015)
Pawel Brach, Alessandro Epasto, Alessandro Panconesi, Piotr Sankowski
Spreading rumours without the network. COSN (2014)
Lorenzo Alvisi, Allen Clement, Alessandro Epasto, Silvio Lattanzi, Alessandro Panconesi
Communities, Random Walks, and Social Sybil Defense. Internet Math. 10 (3-4) (2014)
Alessandro Epasto, Jon Feldman, Silvio Lattanzi, Stefano Leonardi, Vahab S. Mirrokni
Reduce and aggregate: similarity ranking in multi-categorical bipartite graphs. WWW (2014)
Lorenzo Alvisi, Allen Clement, Alessandro Epasto, Silvio Lattanzi, Alessandro Panconesi
SoK: The Evolution of Sybil Defense via Social Networks. IEEE Symposium on Security and Privacy (2013)
Marco Valerio Barbera, Alessandro Epasto, Alessandro Mei, Vasile Claudiu Perta, Julinda Stefa
Signals from the crowd: uncovering social relationships through smartphone probes. Internet Measurement Conference (2013)
Alessandro Epasto, Enrico Nardelli
On a Model for Integrated Information CoRR (2010)