Clustering is a central topic in unsupervised learning and its online formulation has received
a lot of attention in recent years. In this paper, we study the classic facility location problem in …

We consider the classic facility location problem in fully dynamic data streams, where
elements can be both inserted and deleted. In this problem, one is interested in maintaining …

In correlation clustering we are given a set of points along with recommendations whether
each pair of points should be placed in the same cluster or into separate clusters. The goal …

Following the research agenda initiated by Munoz & Vassilvitskii [1] and Lykouris &
Vassilvitskii [2] on learning-augmented online algorithms for classical online optimization …

We study the problem of chasing positive bodies in 1: given a sequence of bodies
K_t=\left{x^t∈R_+^n∣C^tx^t≧1,P^tx^t≦1\right\} revealed online, where C^t and P^t are …

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 …

In submodular covering problems, we are given a monotone, nonnegative submodular
function f: 2 N→ R+ and wish to find the min-cost set S⊆ N such that f (S)= f (N). When f is a …

In the Dynamic Bin Packing problem, n items arrive and depart the system in an online
manner, and the goal is to maintain a good packing throughout. We consider the objective of …

Cloud object stores offer vastly different price points for object storage as a function of
workload and geography. Poor object placement can thus lead to significant cost overheads …

The vector-balancing problem is a fundamental problem in discrepancy theory: given T
vectors in [–1, 1] n, find a signing σ (a)∊{±1} of each vector a to minimize the discrepancy …