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IS
2011
9 years 6 months ago
Fully dynamic metric access methods based on hyperplane partitioning
Metric access methods based on hyperplane partitioning have the advantage, compared to the ballpartitioning-based ones, that regions do not overlap. The price is less flexibility...
Gonzalo Navarro, Roberto Uribe Paredes
JCT
2007
111views more  JCT 2007»
9 years 11 months ago
Lattice point counts for the Shi arrangement and other affinographic hyperplane arrangements
Hyperplanes of the form xj = xi + c are called affinographic. For an affinographic hyperplane arrangement in Rn, such as the Shi arrangement, we study the function f(m) that counts...
David Forge, Thomas Zaslavsky
EOR
2007
104views more  EOR 2007»
9 years 11 months ago
Analysis of the constraint proposal method for two-party negotiations
In the constraint proposal method a mediator locates points at which the two decision makers have joint tangent hyperplanes. We give conditions under which these points are Pareto...
Mitri Kitti, Harri Ehtamo
DCG
2008
86views more  DCG 2008»
9 years 12 months ago
Efficient Algorithms for Maximum Regression Depth
We investigate algorithmic questions that arise in the statistical problem of computing lines or hyperplanes of maximum regression depth among a set of n points. We work primarily...
Marc J. van Kreveld, Joseph S. B. Mitchell, Peter ...
EJC
2010
9 years 12 months ago
Partial covers of PG(n, q)
In this paper, we investigate some properties of partial covers of PG(n, q). We show that a set of q + a hyperplanes, q 81, a < (q - 1)/3, or q > 13 and a (q - 10)/4, that...
Stefan M. Dodunekov, Leo Storme, Geertrui Van de V...
ANOR
2010
119views more  ANOR 2010»
9 years 12 months ago
Alternating local search based VNS for linear classification
We consider the linear classification method consisting of separating two sets of points in d-space by a hyperplane. We wish to determine the hyperplane which minimises the sum of...
Frank Plastria, Steven De Bruyne, Emilio Carrizosa
COMPGEOM
2000
ACM
10 years 4 months ago
Multivariate regression depth
The regression depth of a hyperplane with respect to a set of n points in Rd is the minimum number of points the hyperplane must pass through in a rotation to vertical. We general...
Marshall W. Bern, David Eppstein
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