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An elementary proof of a theorem of Johnson and Lindenstrauss
A result of Johnson and Lindenstrauss [13] shows that a set of n points in high dimensional Euclidean space can be mapped into an O(log n/e2)-dimensional Euclidean space such that the distanceExpand
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Bounded geometries, fractals, and low-distortion embeddings
The doubling constant of a metric space (X, d) is the smallest value /spl lambda/ such that every ball in X can be covered by /spl lambda/ balls of half the radius. The doubling dimension of X isExpand
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Provisioning a virtual private network: a network design problem for multicommodity flow
Consider a setting in which a group of nodes, situated in a large underlying network, wishes to reserve bandwidth on which to support communication. Virtual private networks (VPNs) are services thatExpand
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Robust Submodular Observation Selection
In many applications, one has to actively select among a set of expensive observations before making an informed decision. For example, in environmental monitoring, we want to select locations toExpand
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Approximate clustering without the approximation
Approximation algorithms for clustering points in metric spaces is a flourishing area of research, with much research effort spent on getting a better understanding of the approximation guaranteesExpand
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Simpler and better approximation algorithms for network design
We give simple and easy-to-analyze randomized approximation algorithms for several well-studied NP-hard network design problems. Our algorithms improve over the previously best known approximationExpand
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Iterative Constructions and Private Data Release
In this paper we study the problem of approximately releasing the cut function of a graph while preserving differential privacy, and give new algorithms (and new analyses of existing algorithms) inExpand
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Boosted sampling: approximation algorithms for stochastic optimization
Several combinatorial optimization problems choose elements to minimize the total cost of constructing a feasible solution that satisfies requirements of clients. In the Steiner Tree problem, forExpand
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Constrained Non-monotone Submodular Maximization: Offline and Secretary Algorithms
Constrained submodular maximization problems have long been studied, most recently in the context of auctions and computational advertising, with near-optimal results known under a variety ofExpand
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When LP Is the Cure for Your Matching Woes: Improved Bounds for Stochastic Matchings
Consider a random graph model where each possible edge e is present independently with some probability pe. Given these probabilities, we want to build a large/heavy matching in the randomlyExpand
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