Erik Waingarten

About Erik Waingarten

Erik Waingarten, With an exceptional h-index of 14 and a recent h-index of 13 (since 2020), a distinguished researcher at Columbia University in the City of New York, specializes in the field of theoretical computer science.

His recent articles reflect a diverse array of research interests and contributions to the field:

Near-Linear Time Algorithm for the Chamfer Distance

A Quasi-Monte Carlo Data Structure for Smooth Kernel Evaluations

Data-Dependent LSH for the Earth Mover's Distance

Simple, Scalable and Effective Clustering via One-Dimensional Projections

Fast Algorithms for a New Relaxation of Optimal Transport

Streaming euclidean mst to a constant factor

Estimation of entropy in constant space with improved sample complexity

Finding Monotone Patterns in Sublinear Time, Adaptively

Erik Waingarten Information

University

Position

___

Citations(all)

612

Citations(since 2020)

481

Cited By

332

hIndex(all)

14

hIndex(since 2020)

13

i10Index(all)

17

i10Index(since 2020)

16

Email

University Profile Page

Google Scholar

Erik Waingarten Skills & Research Interests

theoretical computer science

Top articles of Erik Waingarten

Near-Linear Time Algorithm for the Chamfer Distance

Advances in Neural Information Processing Systems

2024/2/13

A Quasi-Monte Carlo Data Structure for Smooth Kernel Evaluations

2024

Moses Charikar
Moses Charikar

H-Index: 36

Erik Waingarten
Erik Waingarten

H-Index: 8

Data-Dependent LSH for the Earth Mover's Distance

arXiv preprint arXiv:2403.05041

2024/3/8

Simple, Scalable and Effective Clustering via One-Dimensional Projections

Advances in Neural Information Processing Systems

2023/12/15

Fast Algorithms for a New Relaxation of Optimal Transport

2023/7/12

Streaming euclidean mst to a constant factor

2023/6/2

Estimation of entropy in constant space with improved sample complexity

Advances in Neural Information Processing Systems

2022/12/6

Finding Monotone Patterns in Sublinear Time, Adaptively

2022/6/28

Omri Ben-Eliezer
Omri Ben-Eliezer

H-Index: 7

Erik Waingarten
Erik Waingarten

H-Index: 8

New streaming algorithms for high dimensional EMD and MST

2022/6/9

The johnson-lindenstrauss lemma for clustering and subspace approximation: From coresets to dimension reduction

arXiv preprint arXiv:2205.00371

2022/5/1

Moses Charikar
Moses Charikar

H-Index: 36

Erik Waingarten
Erik Waingarten

H-Index: 8

Polylogarithmic sketches for clustering

arXiv preprint arXiv:2204.12358

2022/4/26

Moses Charikar
Moses Charikar

H-Index: 36

Erik Waingarten
Erik Waingarten

H-Index: 8

Approximating the distance to monotonicity of boolean functions

Random Structures & Algorithms

2022/3

Sofya Raskhodnikova
Sofya Raskhodnikova

H-Index: 19

Erik Waingarten
Erik Waingarten

H-Index: 8

Learning and testing junta distributions with sub cube conditioning

2021/7/21

Approximate nearest neighbors beyond space partitions

2021

Aleksandar Nikolov
Aleksandar Nikolov

H-Index: 16

Erik Waingarten
Erik Waingarten

H-Index: 8

Random restrictions of high dimensional distributions and uniformity testing with subcube conditioning

2021

Xi Chen
Xi Chen

H-Index: 13

Amit Levi
Amit Levi

H-Index: 7

Erik Waingarten
Erik Waingarten

H-Index: 8

An Improved Analysis of the Quadtree for High Dimensional EMD

2020/11/9

New Methods in Sublinear Computation for High Dimensional Problems

2020

Erik Waingarten
Erik Waingarten

H-Index: 8

Nearly optimal edge estimation with independent set queries

2020

Xi Chen
Xi Chen

H-Index: 13

Amit Levi
Amit Levi

H-Index: 7

Erik Waingarten
Erik Waingarten

H-Index: 8

See List of Professors in Erik Waingarten University(Columbia University in the City of New York)