We present the first constant-factor approximation algorithm for the metric k-median problem. The k-median problem is one of the most well-studied clustering problems, i.e., those...
We consider k-median clustering in finite metric spaces and k-means clustering in Euclidean spaces, in the setting where k is part of the input (not a constant). For the k-means pr...
We study clustering problems in the streaming model, where the goal is to cluster a set of points by making one pass (or a few passes) over the data using a small amount of storag...
—We consider the problem of deploying or repairing a sensor network to guarantee a specified level of multi-path connectivity (k-connectivity) between all nodes. Such a guarante...
Jonathan Bredin, Erik D. Demaine, Mohammad Taghi H...
We give a constant factor approximation algorithm for the following generalization of the k-median problem. We are given a set of clients and facilities in a metric space. Each fa...