activity
20202026
most citedImproved Learning-augmented Algorithms for k-means and k-medians Clustering

3 citations · 9 across the 9 of their papers we have counts for

collaborators

10 papers

cs.DS2026

Edit-Neighboring Data Streams and Privacy under Continual Observation

Joel Daniel Andersson, Anamay Chaturvedi, Monika Henzinger +1

Differential privacy under Continual Observation (CO) quantifies the loss in privacy that occurs when outputs generated using a stream of sensitive input data are published in the…

cs.DS2026

Near-Optimal Generalized Private Testing

Anamay Chaturvedi, Monika Henzinger, Jalaj Upadhyay

In differential privacy (DP), the generalized private testing problem was introduced by Liu and Talwar (STOC 2019). Given a dataset and a sequence of black-box…

cs.LG2022★ 1 cited

Streaming Submodular Maximization with Differential Privacy

Anamay Chaturvedi, Huy Lê Nguyen, Thy Nguyen

In this work, we study the problem of privately maximizing a submodular function in the streaming setting. Extensive work has been done on privately maximizing submodular functions…

cs.LG2022★ 3 cited

Improved Learning-augmented Algorithms for k-means and k-medians Clustering

Thy Nguyen, Anamay Chaturvedi, Huy Lê Nguyen

We consider the problem of clustering in the learning-augmented setting, where we are given a data set in -dimensional Euclidean space, and a label for each data point given by…

cs.IT2022

Universal 1-Bit Compressive Sensing for Bounded Dynamic Range Signals

Sidhant Bansal, Arnab Bhattacharyya, Anamay Chaturvedi +1

A {\em universal 1-bit compressive sensing (CS)} scheme consists of a measurement matrix such that all signals belonging to a particular class can be approximately recovere…

cs.DS2022★ 3 cited

Bounded Space Differentially Private Quantiles

Daniel Alabi, Omri Ben-Eliezer, Anamay Chaturvedi

Estimating the quantiles of a large dataset is a fundamental problem in both the streaming algorithms literature and the differential privacy literature. However, all existing priv…