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Euiwoong Lee

43 papers hereh-index 211.4k citations72 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author4
  • first author5
  • middle author23
  • last author11

Across the 43 of 43 papers where every author was matched, so the position is known.

fields
  • cs.DS31
  • cs.CC9
  • cs.AI1
  • cs.CG1
  • cs.DB1
same name
  • Euiwoong Lee — 20 papers, h 5
  • Euiwoong Lee — 6 papers, h 3
  • Euiwoong Lee — 5 papers, h 1
  • Euiwoong Lee — 2 papers, h 2
  • Euiwoong Lee — 1 paper, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20142023
most citedSum-of-Squares Certificates for Maxima of Random Tensors on the Sphere

14 citations · 51 across the 29 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

cs.DS2019★ 4 cited

Bisect and Conquer: Hierarchical Clustering via Max-Uncut Bisection

Sara Ahmadian, Vaggos Chatziafratis, Alessandro Epasto +4

Hierarchical Clustering is an unsupervised data analysis method which has been widely used for decades. Despite its popularity, it had an underdeveloped analytical foundation and t…

cs.DS2019

The Karger-Stein Algorithm is Optimal for k-cut

Anupam Gupta, Euiwoong Lee, Jason Li

In the k-cut problem, we are given an edge-weighted graph and want to find the least-weight set of edges whose deletion breaks the graph into k connected components. Algorithms…

cs.DS2019

The Number of Minimum k-Cuts: Improving the Karger-Stein Bound

Anupam Gupta, Euiwoong Lee, Jason Li

Given an edge-weighted graph, how many minimum k-cuts can it have? This is a fundamental question in the intersection of algorithms, extremal combinatorics, and graph theory. It…

cs.DS2019

Tight FPT Approximations for k-Median and k-Means

Vincent Cohen-Addad, Anupam Gupta, Amit Kumar +2

We investigate the fine-grained complexity of approximating the classical k-median / k-means clustering problems in general metric spaces. We show how to improve the approximat…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.