Improved non-approximability results for minimum vertex cover with density constraints
Theoretical Computer Science
Bounded Geometries, Fractals, and Low-Distortion Embeddings
FOCS '03 Proceedings of the 44th Annual IEEE Symposium on Foundations of Computer Science
Navigating nets: simple algorithms for proximity search
SODA '04 Proceedings of the fifteenth annual ACM-SIAM symposium on Discrete algorithms
Bypassing the embedding: algorithms for low dimensional metrics
STOC '04 Proceedings of the thirty-sixth annual ACM symposium on Theory of computing
Triangulation and Embedding Using Small Sets of Beacons
FOCS '04 Proceedings of the 45th Annual IEEE Symposium on Foundations of Computer Science
Fast construction of nets in low dimensional metrics, and their applications
SCG '05 Proceedings of the twenty-first annual symposium on Computational geometry
Distance estimation and object location via rings of neighbors
Proceedings of the twenty-fourth annual ACM symposium on Principles of distributed computing
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Small hop-diameter sparse spanners for doubling metrics
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
Fast Construction of Nets in Low-Dimensional Metrics and Their Applications
SIAM Journal on Computing
Searching dynamic point sets in spaces with bounded doubling dimension
Proceedings of the thirty-eighth annual ACM symposium on Theory of computing
Cover trees for nearest neighbor
ICML '06 Proceedings of the 23rd international conference on Machine learning
Routing in Networks with Low Doubling Dimension
ICDCS '06 Proceedings of the 26th IEEE International Conference on Distributed Computing Systems
Local embeddings of metric spaces
Proceedings of the thirty-ninth annual ACM symposium on Theory of computing
Compact routing with slack in low doubling dimension
Proceedings of the twenty-sixth annual ACM symposium on Principles of distributed computing
Ultra-low-dimensional embeddings for doubling metrics
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
Embedding metric spaces in their intrinsic dimension
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
Improved algorithms for fully dynamic geometric spanners and geometric routing
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
Approximating TSP on metrics with bounded global growth
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
Clustering for metric and non-metric distance measures
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
An Optimal Dynamic Spanner for Doubling Metric Spaces
ESA '08 Proceedings of the 16th annual European symposium on Algorithms
Dynamic Routing and Location Services in Metrics of Low Doubling Dimension
DISC '08 Proceedings of the 22nd international symposium on Distributed Computing
Using the doubling dimension to analyze the generalization of learning algorithms
Journal of Computer and System Sciences
Deformable spanners and applications
Computational Geometry: Theory and Applications
Approximation algorithm for the kinetic robust K-center problem
Computational Geometry: Theory and Applications
Distributed spanner construction in doubling metric spaces
OPODIS'06 Proceedings of the 10th international conference on Principles of Distributed Systems
Metric anomaly detection via asymmetric risk minimization
SIMBAD'11 Proceedings of the First international conference on Similarity-based pattern recognition
Efficient regression in metric spaces via approximate lipschitz extension
SIMBAD'13 Proceedings of the Second international conference on Similarity-Based Pattern Recognition
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We introduce a new problem in the study of doubling spaces: Given a point set S and a target dimension d*, remove from S the fewest number of points so that the remaining set has doubling dimension at most d*. We present a bicriteria approximation for this problem, and extend this algorithm to solve a group of proximity problems.