research
∙
08/01/2023
Massively Parallel Algorithms for High-Dimensional Euclidean Minimum Spanning Tree
We study the classic Euclidean Minimum Spanning Tree (MST) problem in th...
share
research
∙
07/14/2023
Differentially Private Clustering in Data Streams
The streaming model is an abstraction of computing over massive data str...
research
∙
04/12/2023
Measuring Re-identification Risk
Compact user representations (such as embeddings) form the backbone of p...
research
∙
01/13/2023
Differentially Private Continual Releases of Streaming Frequency Moment Estimations
The streaming model of computation is a popular approach for working wit...
research
∙
12/05/2022
Stars: Tera-Scale Graph Building for Clustering and Graph Learning
A fundamental procedure in the analysis of massive datasets is the const...
research
∙
07/14/2022
Differentially Private Graph Learning via Sensitivity-Bounded Personalized PageRank
Personalized PageRank (PPR) is a fundamental tool in unsupervised learni...
research
∙
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...
research
∙
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...
research
∙
04/16/2020
Average Case Column Subset Selection for Entrywise ℓ_1-Norm Loss
We study the column subset selection problem with respect to the entrywi...
research
∙
03/02/2020
Connected Components on a PRAM in Log Diameter Time
We present an O(log d + loglog_m/n n)-time randomized PRAM algorithm for...
research
∙
11/05/2019
Parallel Approximate Undirected Shortest Paths Via Low Hop Emulators
We present a (1+ε)-approximate parallel algorithm for computing shortest...
research
∙
10/04/2019
Efficient Symmetric Norm Regression via Linear Sketching
We provide efficient algorithms for overconstrained linear regression pr...
research
∙
10/02/2019
Streaming Balanced Clustering
Clustering of data points in metric space is among the most fundamental ...
research
∙
05/25/2019
Resisting Adversarial Attacks by k-Winners-Take-All
We propose a simple change to the current neural network structure for d...
research
∙
05/02/2019
Log Diameter Rounds Algorithms for 2-Vertex and 2-Edge Connectivity
Many modern parallel systems, such as MapReduce, Hadoop and Spark, can b...
research
∙
02/13/2019
Rethinking Generative Coverage: A Pointwise Guaranteed Approach
All generative models have to combat missing modes. The conventional wis...
research
∙
02/13/2019
Rethinking Generative Coverage: A Pointwise Guaranteed Approac
All generative models have to combat missing modes. The conventional wis...
research
∙
11/04/2018
Towards a Zero-One Law for Entrywise Low Rank Approximation
There are a number of approximation algorithms for NP-hard versions of l...
research
∙
06/17/2018
Subspace Embedding and Linear Regression with Orlicz Norm
We consider a generalization of the classic linear regression problem to...
research
∙
05/19/2018
BourGAN: Generative Networks with Metric Embeddings
This paper addresses the mode collapse for generative adversarial networ...
research
∙
05/08/2018
Parallel Graph Connectivity in Log Diameter Rounds
We study graph connectivity problem in MPC model. On an undirected graph...
research
∙
02/01/2018