The paper revisits the robust s-t path problem, one of the most
fundamen...
While much of network design focuses mostly on cost (number or weight of...
We consider the online unrelated-machine load balancing problem with
rec...
We revisit two well-studied scheduling problems in the unrelated machine...
The active-time scheduling problem considers the problem of scheduling
p...
We study nearly-linear time approximation algorithms for non-preemptive
...
We study a common delivery problem encountered in nowadays online
food-o...
In the Directed Steiner Tree (DST) problem, we are given a directed grap...
Smart cities will be characterized by a variety of intelligent and netwo...
In this paper, we study the problem of estimating latent variable models...
Recently, many machine learning and statistical models such as non-linea...
In this paper we introduce and study the online consistent k-clustering
...
We consider the classic problem of scheduling jobs with precedence
const...
We study the classic problem of scheduling n precedence constrained
unit...
In this paper, we initiate a theoretical study of what we call the join
...
In this paper, we prove topology dependent bounds on the number of round...
In this paper we study the facility location problem in the online with
...
In this paper we study the uncapacitated facility location problem in th...
Directed Steiner Tree (DST) is a central problem in combinatorial
optimi...
Data flow analysis and optimization is considered for homogeneous rectan...
In the Directed Steiner Tree (DST) problem we are given an n-vertex
dire...
In this paper, we consider the k-center/median/means clustering with
out...
We consider stochastic settings for clustering, and develop provably-goo...
We consider the classic scheduling problem of minimizing the total weigh...
Scheduling a set of jobs over a collection of machines is a fundamental
...
In this paper, we give the first constant approximation algorithm for th...
In this paper, we present a novel iterative rounding framework for many
...