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Author Information
Peilin Zhong (Google Research)
Alessandro Epasto (Google)

I am a staff research scientist at Google, New York working in the Graph Mining team part of the Google AI 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. During my Ph.D. studies I was twice an intern at Google Mountain View (2012, 2014) and once at Google NYC (2013). My research interests include algorithmic problems in machine learning and data mining, in particular in the areas of clustering, and large scale graphs analysis.
Vahab Mirrokni (Google Research)
More from the Same Authors
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2023 : Differentially Private Clustering in Data Streams »
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2023 : k-Means Clustering with Distance-Based Privacy »
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2022 Poster: Tight and Robust Private Mean Estimation with Few Users »
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2022 Oral: Tight and Robust Private Mean Estimation with Few Users »
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2022 Poster: Massively Parallel $k$-Means Clustering for Perturbation Resilient Instances »
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2022 Spotlight: Massively Parallel $k$-Means Clustering for Perturbation Resilient Instances »
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2022 : Closing Remarks »
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2022 : Advances in Private Algorithms: Clustering and Graph Mining »
Alessandro Epasto · Peilin Zhong -
2022 : Graph Mining Q/A »
Vahab Mirrokni -
2022 : New Challenges in Graph Mining: Scalability, Stability, and Privacy Applications »
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2022 Expo Talk Panel: Challenges Of Applying Graph Neural Networks »
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2022 : Graph Mining at Google »
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2021 Poster: Hierarchical Agglomerative Graph Clustering in Nearly-Linear Time »
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2021 Spotlight: Hierarchical Agglomerative Graph Clustering in Nearly-Linear Time »
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2021 Poster: Regularized Online Allocation Problems: Fairness and Beyond »
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2021 Spotlight: Regularized Online Allocation Problems: Fairness and Beyond »
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2021 Poster: Revenue-Incentive Tradeoffs in Dynamic Reserve Pricing »
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2021 Spotlight: Revenue-Incentive Tradeoffs in Dynamic Reserve Pricing »
Yuan Deng · Sébastien Lahaie · Vahab Mirrokni · Song Zuo -
2020 Poster: Robust Pricing in Dynamic Mechanism Design »
Yuan Deng · Sébastien Lahaie · Vahab Mirrokni -
2020 Poster: Dual Mirror Descent for Online Allocation Problems »
Santiago Balseiro · Haihao Lu · Vahab Mirrokni -
2020 Poster: Bandits with Adversarial Scaling »
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2019 Poster: Non-monotone Submodular Maximization with Nearly Optimal Adaptivity and Query Complexity »
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2019 Poster: Categorical Feature Compression via Submodular Optimization »
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2019 Oral: Categorical Feature Compression via Submodular Optimization »
Mohammad Hossein Bateni · Lin Chen · Hossein Esfandiari · Thomas Fu · Vahab Mirrokni · Afshin Rostamizadeh -
2019 Oral: Non-monotone Submodular Maximization with Nearly Optimal Adaptivity and Query Complexity »
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2019 Poster: Distributed Weighted Matching via Randomized Composable Coresets »
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2019 Oral: Distributed Weighted Matching via Randomized Composable Coresets »
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2018 Poster: Parallel and Streaming Algorithms for K-Core Decomposition »
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2018 Poster: Accelerating Greedy Coordinate Descent Methods »
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2018 Poster: Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions »
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2018 Oral: Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions »
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2018 Oral: Accelerating Greedy Coordinate Descent Methods »
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2018 Oral: Parallel and Streaming Algorithms for K-Core Decomposition »
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2018 Poster: Proportional Allocation: Simple, Distributed, and Diverse Matching with High Entropy »
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2018 Oral: Proportional Allocation: Simple, Distributed, and Diverse Matching with High Entropy »
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2017 Poster: Tight Bounds for Approximate Carathéodory and Beyond »
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2017 Talk: Tight Bounds for Approximate Carathéodory and Beyond »
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