Euiwoong Lee

works on

approximation algorithms 1 dual fitting 1 euclidean metrics 1 k-means clustering 1 spectral analysis 1

From the 1 of 5 linked papers with an AI index.

most citedAccelerating Scientific Research with Gemini: Case Studies and Common Techniques

3 citations · 3 across the 4 of their papers we have counts for

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cs.DS2026

Spectral Dual Fitting for $k$ -Means

Aditya Anand, Moses Charikar, Vincent Cohen-Addad +5

The paper introduces a new dual‑fitting algorithm that achieves better approximation ratios for the k‑means clustering problem in both Euclidean and general metric spaces, using a…

cs.DS2026

An Improved Greedy Approximation for (Metric) $k$ -Means

Moses Charikar, Vincent Cohen-Addad, Ruiquan Gao +3

Clustering is a basic task in data analysis and machine learning, and the optimization of clustering objectives are well-studied optimization problems; amongst these, the $k$ -Means…

cs.DS2026

A $(2 + ε)$ -Approximation Algorithm for Metric $k$ -Median

Vincent Cohen-Addad, Fabrizio Grandoni, Euiwoong Lee +2

In the classical NP-hard metric $k$ -median problem, we are given a set of $n$ clients and centers with metric distances between them, along with an integer parameter $k \geq 1$ . The…

cs.DS2025

On Approximability of $ℓ_{2}^{2}$ Min-Sum Clustering

Karthik C. S., Euiwoong Lee, Yuval Rabani +2

The $ℓ_{2}^{2}$ min-sum $k$ -clustering problem is to partition an input set into clusters $C_{1}, \dots, C_{k}$ to minimize $\sum_{i = 1}^{k} \sum_{p, q \in C_{i}} ∥ p - q ∥_{2}^{2}$ . Although $\ell_2^2…

Spectral Dual Fitting for k-Means

An Improved Greedy Approximation for (Metric) k-Means

A (2+ε)-Approximation Algorithm for Metric k-Median

On Approximability of ℓ22​ Min-Sum Clustering

Spectral Dual Fitting for $k$ -Means

An Improved Greedy Approximation for (Metric) $k$ -Means

A $(2 + ε)$ -Approximation Algorithm for Metric $k$ -Median

On Approximability of $ℓ_{2}^{2}$ Min-Sum Clustering