The bin packing problem is a well-studied problem in combinatorial optimization. In the
classical bin packing problem, we are given a list of real numbers in (0, 1] and the goal is to …

Dependent rounding is a useful technique for optimization problems with hard budget
constraints. This framework naturally leads to negative correlation properties. However, what …

We design new approximation algorithms for the problems of optimizing submodular and
supermodular functions subject to a single matroid constraint. Specifically, we consider the …

The study of combinatorial problems with a submodular objective function has attracted
much attention in recent years, and is partly motivated by the importance of such problems to …

We consider the problem of randomly rounding a fractional solution x in an integer polytope
P⊆[0, 1] n to a vertex X of P, so that E [X]= x. Our goal is to achieve concentration properties …

The fair-ranking problem, which asks to rank a given set of items to maximize utility subject
to group fairness constraints, has received attention in the fairness, information retrieval, and …

Algorithms for approximating the nondominated set of multiobjective optimization problems
are reviewed. The approaches are categorized into general methods that are applicable …

We introduce the abstract problem of rounding an unknown fractional bipartite b-matching x
revealed online (eg, output by an online fractional algorithm), exposed node-by-node on …

A wide variety of problems in machine learning, including exemplar clustering, document
summarization, and sensor placement, can be cast as constrained submodular …

Suppose that we have n agents and n items which lie in a shared metric space. We would
like to match the agents to items such that the total distance from agents to their matched …