Maryam Negahbani

activity

20182021

most citedBetter Algorithms for Individually Fair

k

-Clustering

5 citations · 5 across the 1 of their papers we have counts for

collaborators

4 papers

cs.DS2021★ 5 cited

Better Algorithms for Individually Fair $k$ -Clustering

Deeparnab Chakrabarty, Maryam Negahbani

We study data clustering problems with $ℓ_{p}$ -norm objectives (e.g. $k$ -Median and $k$ -Means) in the context of individual fairness. The dataset consists of $n$ points, and we wa…

cs.DS2021

Robust $k$ -Center with Two Types of Radii

Deeparnab Chakrabarty, Maryam Negahbani

In the non-uniform $k$ -center problem, the objective is to cover points in a metric space with specified number of balls of different radii. Chakrabarty, Goyal, and Krishnaswamy [I…

cs.DS2019

Fair Algorithms for Clustering

Suman K. Bera, Deeparnab Chakrabarty, Nicolas J. Flores +1

We study the problem of finding low-cost Fair Clusterings in data where each data point may belong to many protected groups. Our work significantly generalizes the seminal work of…

cs.DS2018

Generalized Center Problems with Outliers

Deeparnab Chakrabarty, Maryam Negahbani

We study the $F$ -center problem with outliers: given a metric space $(X, d)$ , a general down-closed family $F$ of subsets of $X$ , and a parameter $m$ , we need to…

Better Algorithms for Individually Fair k-Clustering

Robust k-Center with Two Types of Radii

Fair Algorithms for Clustering

Generalized Center Problems with Outliers

Better Algorithms for Individually Fair $k$ -Clustering

Robust $k$ -Center with Two Types of Radii