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Alessandro Epasto
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- affiliation: Google, New York, NY, USA
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2020 – today
- 2024
- [c39]MohammadHossein Bateni, Vincent Cohen-Addad, Alessandro Epasto, Silvio Lattanzi:
A Scalable Algorithm for Individually Fair k-Means Clustering. AISTATS 2024: 3151-3159 - [c38]Vincent Cohen-Addad, Tommaso d'Orsi, Alessandro Epasto, Vahab Mirrokni, Peilin Zhong:
Perturb-and-Project: Differentially Private Similarities and Marginals. ICML 2024 - [c37]Alessandro Epasto
, Hossein Esfandiari
Smooth Anonymity for Sparse Graphs. WWW (Companion Volume) 2024: 621-624 - [i24]MohammadHossein Bateni, Vincent Cohen-Addad, Alessandro Epasto, Silvio Lattanzi:
A Scalable Algorithm for Individually Fair K-means Clustering. CoRR abs/2402.06730 (2024) - [i23]Vincent Cohen-Addad, Tommaso d'Orsi, Alessandro Epasto, Vahab Mirrokni, Peilin Zhong:
Perturb-and-Project: Differentially Private Similarities and Marginals. CoRR abs/2406.04868 (2024) - [i22]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 abs/2406.11206 (2024) - [i21]Alessandro Epasto, Quanquan C. Liu, Tamalika Mukherjee, Felix Zhou:
The Power of Graph Sparsification in the Continual Release Model. CoRR abs/2407.17619 (2024) - 2023
- [j5]CJ Carey
Measuring Re-identification Risk. Proc. ACM Manag. Data 1(2): 149:1-149:26 (2023) - [c36]Jacob Imola, Alessandro Epasto, Mohammad Mahdian, Vincent Cohen-Addad, Vahab Mirrokni:
Differentially Private Hierarchical Clustering with Provable Approximation Guarantees. ICML 2023: 14353-14375 - [c35]Alessandro Epasto, Jieming Mao, Andres Muñoz Medina, Vahab Mirrokni, Sergei Vassilvitskii, Peilin Zhong:
Differentially Private Continual Releases of Streaming Frequency Moment Estimations. ITCS 2023: 48:1-48:24 - [c34]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 - [c33]Alessandro Epasto, Vahab Mirrokni, Shyam Narayanan, Peilin Zhong:
k-Means Clustering with Distance-Based Privacy. NeurIPS 2023 - [i20]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 abs/2301.04822 (2023) - [i19]Alessandro Epasto, Jieming Mao, Andres Muñoz Medina, Vahab Mirrokni, Sergei Vassilvitskii, Peilin Zhong:
Differentially Private Continual Releases of Streaming Frequency Moment Estimations. CoRR abs/2301.05605 (2023) - [i18]Jacob Imola, Alessandro Epasto, Mohammad Mahdian, Vincent Cohen-Addad, Vahab Mirrokni:
Differentially-Private Hierarchical Clustering with Provable Approximation Guarantees. CoRR abs/2302.00037 (2023) - [i17]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 abs/2304.07210 (2023) - [i16]Alessandro Epasto, Tamalika Mukherjee, Peilin Zhong:
Differentially Private Clustering in Data Streams. CoRR abs/2307.07449 (2023) - 2022
- [c32]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: 221-230 - [c31]Vincent Cohen-Addad, Alessandro Epasto, Vahab Mirrokni, Shyam Narayanan, Peilin Zhong:
Near-Optimal Private and Scalable $k$-Clustering. NeurIPS 2022 - [c30]Alessandro Epasto, Vahab Mirrokni, Bryan Perozzi, Anton Tsitsulin, Peilin Zhong:
Differentially Private Graph Learning via Sensitivity-Bounded Personalized PageRank. NeurIPS 2022 - [c29]Alessandro Epasto, Mohammad Mahdian, Vahab S. Mirrokni, Peilin Zhong:
Massively Parallel and Dynamic Algorithms for Minimum Size Clustering. SODA 2022: 1613-1660 - [c28]Alessandro Epasto, Mohammad Mahdian, Vahab S. Mirrokni, Peilin Zhong:
Improved Sliding Window Algorithms for Clustering and Coverage via Bucketing-Based Sketches. SODA 2022: 3005-3042 - [c27]Matteo Almanza, Alessandro Epasto, Alessandro Panconesi, Giuseppe Re:
k-Clustering with Fair Outliers. WSDM 2022: 5-15 - [i15]Vincent Cohen-Addad, Alessandro Epasto, Silvio Lattanzi, Vahab S. Mirrokni, Andres Muñoz Medina, David Saulpic, Chris Schwiegelshohn, Sergei Vassilvitskii:
Scalable Differentially Private Clustering via Hierarchically Separated Trees. CoRR abs/2206.08646 (2022) - [i14]Hossein Esfandiari, Alessandro Epasto, Vahab S. Mirrokni, Andres Muñoz Medina, Sergei Vassilvitskii:
Smooth Anonymity for Sparse Binary Matrices. CoRR abs/2207.06358 (2022) - [i13]Alessandro Epasto, Vahab Mirrokni, Bryan Perozzi, Anton Tsitsulin, Peilin Zhong:
Differentially Private Graph Learning via Sensitivity-Bounded Personalized PageRank. CoRR abs/2207.06944 (2022) - 2021
- [c26]Alessandro Epasto, Andrés Muñoz Medina, Steven Avery, Yijian Bai, Róbert Busa-Fekete, CJ 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: 2802-2810 - [i12]Alessandro Epasto, Mohammad Mahdian, Vahab S. Mirrokni, Peilin Zhong:
Massively Parallel and Dynamic Algorithms for Minimum Size Clustering. CoRR abs/2106.02685 (2021) - [i11]Alessandro Epasto, Mohammad Mahdian, Vahab S. Mirrokni, Peilin Zhong:
Improved Sliding Window Algorithms for Clustering and Coverage via Bucketing-Based Sketches. CoRR abs/2110.15533 (2021) - 2020
- [c25]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: 3121-3132 - [c24]Sara Ahmadian, Alessandro Epasto, Ravi Kumar, Mohammad Mahdian:
Fair Correlation Clustering. AISTATS 2020: 4195-4205 - [c23]Sara Ahmadian, Alessandro Epasto, Marina Knittel, Ravi Kumar, Mohammad Mahdian, Benjamin Moseley, Philip Pham, Sergei Vassilvitskii, Yuyan Wang:
Fair Hierarchical Clustering. NeurIPS 2020 - [c22]Michele Borassi, Alessandro Epasto, Silvio Lattanzi, Sergei Vassilvitskii, Morteza Zadimoghaddam:
Sliding Window Algorithms for k-Clustering Problems. NeurIPS 2020 - [c21]Alessandro Epasto, Mohammad Mahdian, Jieming Mao, Vahab S. Mirrokni, Lijie Ren:
Smoothly Bounding User Contributions in Differential Privacy. NeurIPS 2020 - [c20]Alessandro Epasto, Mohammad Mahdian, Vahab S. Mirrokni, Emmanouil Zampetakis
Optimal Approximation - Smoothness Tradeoffs for Soft-Max Functions. NeurIPS 2020 - [i10]Sara Ahmadian, Alessandro Epasto
Fair Correlation Clustering. CoRR abs/2002.02274 (2020) - [i9]Michele Borassi, Alessandro Epasto, Silvio Lattanzi, Sergei Vassilvitskii, Morteza Zadimoghaddam:
Sliding Window Algorithms for k-Clustering Problems. CoRR abs/2006.05850 (2020) - [i8]Sara Ahmadian, Alessandro Epasto, Marina Knittel, Ravi Kumar, Mohammad Mahdian, Benjamin Moseley, Philip Pham, Sergei Vassilvitskii, Yuyan Wang:
Fair Hierarchical Clustering. CoRR abs/2006.10221 (2020) - [i7]Alessandro Epasto, Mohammad Mahdian, Vahab S. Mirrokni, Manolis Zampetakis:
Optimal Approximation - Smoothness Tradeoffs for Soft-Max Functions. CoRR abs/2010.11450 (2020)
2010 – 2019
- 2019
- [c19]Sara Ahmadian, Alessandro Epasto
Clustering without Over-Representation. KDD 2019: 267-275 - [c18]Michele Borassi, Alessandro Epasto
Better Sliding Window Algorithms to Maximize Subadditive and Diversity Objectives. PODS 2019: 254-268 - [c17]Alessandro Epasto
Scalable Diversity Maximization via Small-size Composable Core-sets (Brief Announcement). SPAA 2019: 41-42 - [c16]Alessandro Epasto
Is a Single Embedding Enough? Learning Node Representations that Capture Multiple Social Contexts. WWW 2019: 394-404 - [c15]Alessandro Epasto
On-Device Algorithms for Public-Private Data with Absolute Privacy. WWW 2019: 405-416 - [i6]Alessandro Epasto, Bryan Perozzi:
Is a Single Embedding Enough? Learning Node Representations that Capture Multiple Social Contexts. CoRR abs/1905.02138 (2019) - [i5]Sara Ahmadian, Alessandro Epasto, Ravi Kumar, Mohammad Mahdian:
Clustering without Over-Representation. CoRR abs/1905.12753 (2019) - [i4]Sara Ahmadian, Vaggos Chatziafratis, Alessandro Epasto
Bisect and Conquer: Hierarchical Clustering via Max-Uncut Bisection. CoRR abs/1912.06983 (2019) - 2018
- [j4]Alessandro Epasto
Efficient Approximation for Restricted Biclique Cover Problems. Algorithms 11(6): 84 (2018) - [c14]Alessandro Epasto, Mohammad Mahdian, Vahab S. Mirrokni, Song Zuo:
Incentive-Aware Learning for Large Markets. WWW 2018: 1369-1378 - 2017
- [j3]Lorenzo De Stefani, Alessandro Epasto
TRIÈST: Counting Local and Global Triangles in Fully Dynamic Streams with Fixed Memory Size. ACM Trans. Knowl. Discov. Data 11(4): 43:1-43:50 (2017) - [c13]Alessandro Epasto
Real-Time Targeted-Influence Queries over Large Graphs. ASONAM 2017: 224-231 - [c12]Alessandro Epasto
Ego-Splitting Framework: from Non-Overlapping to Overlapping Clusters. KDD 2017: 145-154 - [c11]Alessandro Epasto
Bicriteria Distributed Submodular Maximization in a Few Rounds. SPAA 2017: 25-33 - [c10]Alessandro Epasto
Submodular Optimization Over Sliding Windows. WWW 2017: 421-430 - [c9]David Stück, Haraldur Tómas Hallgrímsson, Greg Ver Steeg, Alessandro Epasto
The Spread of Physical Activity Through Social Networks. WWW 2017: 519-528 - 2016
- [c8]Lorenzo De Stefani, Alessandro Epasto, Eli Upfal, Fabio Vandin:
Reconstructing Hidden Permutations Using the Average-Precision (AP) Correlation Statistic. AAAI 2016: 1526-1532 - [c7]Lorenzo De Stefani, Alessandro Epasto
TRIÈST: Counting Local and Global Triangles in Fully-Dynamic Streams with Fixed Memory Size. KDD 2016: 825-834 - [i3]Lorenzo De Stefani, Alessandro Epasto, Matteo Riondato, Eli Upfal:
TRIÈST: Counting Local and Global Triangles in Fully-dynamic Streams with Fixed Memory Size. CoRR abs/1602.07424 (2016) - [i2]Alessandro Epasto, Silvio Lattanzi, Sergei Vassilvitskii, Morteza Zadimoghaddam:
Submodular Optimization over Sliding Windows. CoRR abs/1610.09984 (2016) - 2015
- [j2]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): 324-335 (2015) - [c6]Flavio Chierichetti, Alessandro Epasto
Efficient Algorithms for Public-Private Social Networks. KDD 2015: 139-148 - [c5]Alessandro Epasto
Efficient Densest Subgraph Computation in Evolving Graphs. WWW 2015: 300-310 - 2014
- [j1]Lorenzo Alvisi, Allen Clement, Alessandro Epasto, Silvio Lattanzi, Alessandro Panconesi:
Communities, Random Walks, and Social Sybil Defense. Internet Math. 10(3-4): 360-420 (2014) - [c4]Pawel Brach, Alessandro Epasto, Alessandro Panconesi, Piotr Sankowski:
Spreading rumours without the network. COSN 2014: 107-118 - [c3]Alessandro Epasto
Reduce and aggregate: similarity ranking in multi-categorical bipartite graphs. WWW 2014: 349-360 - 2013
- [c2]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: 265-276 - [c1]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: 382-396 - 2010
- [i1]Alessandro Epasto, Enrico Nardelli:
On a Model for Integrated Information. CoRR abs/1001.0063 (2010)
Coauthor Index
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