In this work, we study fairness in centroid clustering. In this problem, k cluster centers must
be placed given n points in a metric space, and the cost to each point is its distance to the …

We present a refined construction of hierarchical probabilistic partitions with novel
properties, substantially stronger than previously known. Our construction provides a family …

In the Priority $ k $-Center problem, the input consists of a metric space $(X, d) $, an integer
$ k $, and for each point $ v\in X $ a priority radius $ r (v) $. The goal is to choose $ k …

The clustering problem has been paid lots of attention in various fields of compute science.
However, in many applications, the existence of noisy data poses a big challenge for the …

The squared metric k-facility location problem is a frequently encountered generalization of
the k-means problem, where a specific cost should be paid for opening each facility. The …

The explosive growth of global distributed services has led to a massive increase in bulk
multicast data transfers over the inter-datacenter Wide-Area Network. While many solutions …

In this paper, we study the squared metric k-facility location problem, which generalizes the k-
means problem in that each facility has a specific cost of opening it in the solution. The …

Designing decision-making algorithms that treat people fairly, use limited resources
efficiently, and foster social good is of high importance. We contribute toward this direction …

Motivated by an application from geodesy, we study the connected k-center problem and the
connected k-diameter problem. The former problem has been introduced by Ge et al.(ACM …

Game-theoretic solution concepts provide a sound notion of rational behavior in multiagent
settings. To operationalize them, they have to be accompanied by techniques to compute …