8 citations · 26 across the 17 of their papers we have counts for
19 papers · 1 filter
Massively Parallel Algorithms for High-Dimensional Euclidean Minimum Spanning Tree
Rajesh Jayaram, Vahab Mirrokni, Shyam Narayanan +1
We study the classic Euclidean Minimum Spanning Tree (MST) problem in the Massively Parallel Computation (MPC) model. Given a set of points, the goal i…
The Full Landscape of Robust Mean Testing: Sharp Separations between Oblivious and Adaptive Contamination
Clément L. Canonne, Samuel B. Hopkins, Jerry Li +2
We consider the question of Gaussian mean testing, a fundamental task in high-dimensional distribution testing and signal processing, subject to adversarial corruptions of the samp…
Improved Diversity Maximization Algorithms for Matching and Pseudoforest
Sepideh Mahabadi, Shyam Narayanan
In this work we consider the diversity maximization problem, where given a data set of elements, and a parameter , the goal is to pick a subset of of size maximi…
Data Structures for Density Estimation
Anders Aamand, Alexandr Andoni, Justin Y. Chen +3
We study statistical/computational tradeoffs for the following density estimation problem: given distributions over a discrete domain of size , and sampli…
Learned Interpolation for Better Streaming Quantile Approximation with Worst-Case Guarantees
Nicholas Schiefer, Justin Y. Chen, Piotr Indyk +3
An -approximate quantile sketch over a stream of inputs approximates the rank of any query point - that is, the number of input points less than - up to an…
Krylov Methods are (nearly) Optimal for Low-Rank Approximation
Ainesh Bakshi, Shyam Narayanan
We consider the problem of rank- low-rank approximation (LRA) in the matrix-vector product model under various Schatten norms: $$ \min_{\|u\|_2=1} \|A (I - u u^\top)\|_{\mathcal…