We study the consistent k-center clustering problem. In this problem, the goal is to maintain a
constant factor approximate k-center solution during a sequence of n point insertions and …

Abstract We present a $ O (1) $-approximate fully dynamic algorithm for the $ k $-median
and $ k $-means problems on metric spaces with amortized update time $\tilde O (k) $ and …

Given a point set $ P\subseteq M $ from a metric space $(M, d) $ and numbers $ k, z\in N $,
the* metric $ k $-center problem with $ z $ outliers* is to find a set $ C^\ast\subseteq P $ of …

The edit distance is a fundamental measure of sequence similarity, defined as the minimum
number of character insertions, deletions, and substitutions needed to transform one string …

In this paper we give the first efficient algorithms for the k-center problem on dynamic graphs
undergoing edge updates. In this problem, the goal is to partition the input into k sets by …

Given points from an arbitrary metric space and a sequence of point updates sent by an
adversary, what is the minimum recourse per update (ie, the minimum number of changes …

In the dynamic metric $ k $-median problem, we wish to maintain a set of $ k $ centers $
S\subseteq V $ in an input metric space $(V, d) $ that gets updated via point …

We present deterministic approximation algorithms for some variants of center-based
clustering and related problems in the fully dynamic setting, where the pointset evolves …

We study the distributed tracking model, also known as distributed functional monitoring.
This model involves $ k $ sites each receiving a stream of items and communicating with the …

In the dynamic metric k-median problem, we wish to maintain a set of k centers S⊆V in an
input metric space (V,d) that gets updated via point insertions/deletions, so as to minimize …