M
MohammadHossein Bateni
Researcher at Google
Publications - 88
Citations - 1896
MohammadHossein Bateni is an academic researcher from Google. The author has contributed to research in topics: Approximation algorithm & Steiner tree problem. The author has an hindex of 24, co-authored 83 publications receiving 1656 citations. Previous affiliations of MohammadHossein Bateni include Princeton University & Sharif University of Technology.
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Journal ArticleDOI
Submodular secretary problem and extensions
TL;DR: This article considers a very general setting of the classic secretary problem, in which the goal is to select k secretaries so as to maximize the expectation of a submodular function which defines efficiency of the selected secretarial group based on their overlapping skills, and presents the first constant-competitive algorithm for this case.
Journal ArticleDOI
Approximation Schemes for Steiner Forest on Planar Graphs and Graphs of Bounded Treewidth
TL;DR: It is shown that Steiner forest can be solved in polynomial time for series-parallel graphs (graphs of treewidth at most two) by a novel combination of dynamic programming and minimum cut computations, completing the thorough complexity study of Steiner Forest in the range of bounded-treewidth graphs, planar graphs, and bounded-genus graphs.
Journal ArticleDOI
Improved Approximation Algorithms for Prize-Collecting Steiner Tree and TSP
TL;DR: (2-epsilon)-approximation algorithms for all three problems of the Steiner tree, traveling salesman, and stroll are presented, connected by a unified technique for improving prize-collecting algorithms that allows us to circumvent the integrality gap barrier.
Proceedings ArticleDOI
MaxMin allocation via degree lower-bounded arborescences
TL;DR: The results imply a rounding algorithm for the relaxations obtained by t rounds of the Sherali-Adams hierarchy applied to a natural LP relaxation of the problem, and a much simpler LP is presented which is equivalent in power to the configuration LP.
Proceedings Article
Affinity Clustering: Hierarchical Clustering at Scale
MohammadHossein Bateni,Soheil Behnezhad,Mahsa Derakhshan,MohammadTaghi Hajiaghayi,Raimondas Kiveris,Silvio Lattanzi,Vahab Mirrokni +6 more
TL;DR: This work proposes affinity, a novel hierarchical clustering based on Boruvka's MST algorithm, and proves certain theoretical guarantees for affinity and shows that in practice it is superior to several other state-of-the-art clustering algorithms.