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07/14/2023
Differentially Private Clustering in Data Streams
The streaming model is an abstraction of computing over massive data str...
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04/12/2023
Measuring Re-identification Risk
Compact user representations (such as embeddings) form the backbone of p...
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01/31/2023
Differentially-Private Hierarchical Clustering with Provable Approximation Guarantees
Hierarchical Clustering is a popular unsupervised machine learning metho...
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01/13/2023
Differentially Private Continual Releases of Streaming Frequency Moment Estimations
The streaming model of computation is a popular approach for working wit...
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01/11/2023
Private estimation algorithms for stochastic block models and mixture models
We introduce general tools for designing efficient private estimation al...
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07/14/2022
Differentially Private Graph Learning via Sensitivity-Bounded Personalized PageRank
Personalized PageRank (PPR) is a fundamental tool in unsupervised learni...
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07/13/2022
Smooth Anonymity for Sparse Binary Matrices
When working with user data providing well-defined privacy guarantees is...
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06/17/2022
Scalable Differentially Private Clustering via Hierarchically Separated Trees
We study the private k-median and k-means clustering problem in d dimens...
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10/29/2021
Improved Sliding Window Algorithms for Clustering and Coverage via Bucketing-Based Sketches
Streaming computation plays an important role in large-scale data analys...
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06/04/2021
Massively Parallel and Dynamic Algorithms for Minimum Size Clustering
In this paper, we study the r-gather problem, a natural formulation of m...
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10/22/2020
Optimal Approximation – Smoothness Tradeoffs for Soft-Max Functions
A soft-max function has two main efficiency measures: (1) approximation ...
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06/18/2020
Fair Hierarchical Clustering
As machine learning has become more prevalent, researchers have begun to...
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06/10/2020
Sliding Window Algorithms for k-Clustering Problems
The sliding window model of computation captures scenarios in which data...
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02/06/2020
Fair Correlation Clustering
In this paper, we study correlation clustering under fairness constraint...
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12/15/2019
Bisect and Conquer: Hierarchical Clustering via Max-Uncut Bisection
Hierarchical Clustering is an unsupervised data analysis method which ha...
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05/29/2019
Clustering without Over-Representation
In this paper we consider clustering problems in which each point is end...
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05/06/2019
Is a Single Embedding Enough? Learning Node Representations that Capture Multiple Social Contexts
Recent interest in graph embedding methods has focused on learning a sin...
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12/31/2009