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Book ChapterDOI

Competitive Weighted Matching in Transversal Matroids

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TLDR
An algorithm is presented that processes a uniformly random permutation of the left-vertices, one left-vertex at a time, and the weight of the matching returned is within a constant factor of that of a maximum weight matching.
Abstract
Consider a bipartite graph with a set of left-vertices and a set of right-vertices. All the edges adjacent to the same left-vertex have the same weight. We present an algorithm that, given the set of right-vertices and the number of left-vertices, processes a uniformly random permutation of the left-vertices, one left-vertex at a time. In processing a particular left-vertex, the algorithm either permanently matches the left-vertex to a thus-far unmatched right-vertex, or decides never to match the left-vertex. The weight of the matching returned by our algorithm is within a constant factor of that of a maximum weight matching.

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Book

Online Matching and Ad Allocation

TL;DR: This monograph surveys the key problems, models and algorithms from online matchings, as well as their implication in the practice of ad allocation, to provide a classification of the problems, techniques and algorithms in this area.
Proceedings ArticleDOI

Matroid prophet inequalities

TL;DR: In this paper, the prophet inequality of Krengel, Sucheston, and Garling has been generalized to the matroid setting, where the prophet and the gambler are allowed to make more than one selection subject to a matroid constraint.
Journal ArticleDOI

Online auctions and generalized secretary problems

TL;DR: This work presents generalized secretary problems as a framework for online auctions, and presents surprisingly strong constant factor guarantees on the expected value of solutions obtained by online algorithms.
Book ChapterDOI

Constrained non-monotone submodular maximization: offline and secretary algorithms

TL;DR: In this article, a greedy-based constant factor algorithm for non-monotone submodular maximization subject to a knapsack constraint and a secretary constraint was proposed.
Proceedings ArticleDOI

Online vertex-weighted bipartite matching and single-bid budgeted allocations

TL;DR: In this paper, an optimal (1−1/e)-competitive randomized algorithm for general vertex weights was proposed, which is the first known generalization of the algorithm in this model and provides new insights into the role of randomization in online allocation problems.
References
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Book

Online Computation and Competitive Analysis

TL;DR: This book discusses competitive analysis and decision making under uncertainty in the context of the k-server problem, which involves randomized algorithms in order to solve the problem of paging.
Proceedings ArticleDOI

An optimal algorithm for on-line bipartite matching

TL;DR: This work applies the general approach to data structures, bin packing, graph coloring, and graph coloring to bipartite matching and shows that a simple randomized on-line algorithm achieves the best possible performance.
Journal ArticleDOI

Who Solved the Secretary Problem

TL;DR: The object of this article is to give a fresh view of the origins of the problem, touching upon Cayley and Kepler, and review of the field (listing the subfields of recent interest), partly serious (to answer the question posed in the title), and partly entertainment.
Journal ArticleDOI

The Secretary Problem and its Extensions: A Review

TL;DR: In this article, the development of what has come to be known as the secretary problem is traced from its origins in the early 1960's and all published work to date on the problem and its extensions is reviewed.