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109
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CCCG
2007
15 years 2 months ago
Approximating k-hop Minimum Spanning Trees in Euclidean Metrics
In the minimum-cost k-hop spanning tree (k-hop MST) problem, we are given a set S of n points in a metric space, a positive small integer k and a root point r ∈ S. We are intere...
Sören Laue, Domagoj Matijevic
99
Voted
ICML
2007
IEEE
16 years 1 months ago
Information-theoretic metric learning
In this paper, we present an information-theoretic approach to learning a Mahalanobis distance function. We formulate the problem as that of minimizing the differential relative e...
Jason V. Davis, Brian Kulis, Prateek Jain, Suvrit ...
101
Voted
KDD
2006
ACM
142views Data Mining» more  KDD 2006»
16 years 1 months ago
Mining distance-based outliers from large databases in any metric space
Let R be a set of objects. An object o R is an outlier, if there exist less than k objects in R whose distances to o are at most r. The values of k, r, and the distance metric ar...
Yufei Tao, Xiaokui Xiao, Shuigeng Zhou
ICCAD
2003
IEEE
152views Hardware» more  ICCAD 2003»
15 years 9 months ago
Dynamic Fault-Tolerance and Metrics for Battery Powered, Failure-Prone Systems
Emerging VLSI technologies and platforms are giving rise to systems with inherently high potential for runtime failure. Such failures range from intermittent electrical and mechan...
Phillip Stanley-Marbell, Diana Marculescu
TACAS
2004
Springer
139views Algorithms» more  TACAS 2004»
15 years 6 months ago
Error Explanation with Distance Metrics
Abstract In the event that a system does not satisfy a specification, a model checker will typically automatically produce a counterexample trace that shows a particular instance ...
Alex Groce