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» On the Hamkins approximation property
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FLAIRS
2006
15 years 7 months ago
Sensitivity Analysis of Markovian Models
Sensitivity analysis of Markovian models amounts to computing the constants in polynomial functions of a parameter under study. To handle the computational complexity involved, we...
Theodore Charitos, Linda C. van der Gaag
EUSFLAT
2003
187views Fuzzy Logic» more  EUSFLAT 2003»
15 years 7 months ago
Edge orientation-based fuzzy Hough transform (EOFHT)
The Hough Transform [6] -HT- is a standard tool in image analysis that allows recognizing global patterns in an image space. To detect shapes in noisy data, preserving the idea of...
Eduard Montseny, Pilar Sobrevilla, Pere Marè...
NIPS
2004
15 years 7 months ago
Triangle Fixing Algorithms for the Metric Nearness Problem
Various problems in machine learning, databases, and statistics involve pairwise distances among a set of objects. It is often desirable for these distances to satisfy the propert...
Inderjit S. Dhillon, Suvrit Sra, Joel A. Tropp
NIPS
2004
15 years 7 months ago
Log-concavity Results on Gaussian Process Methods for Supervised and Unsupervised Learning
Log-concavity is an important property in the context of optimization, Laplace approximation, and sampling; Bayesian methods based on Gaussian process priors have become quite pop...
Liam Paninski
SODA
2004
ACM
151views Algorithms» more  SODA 2004»
15 years 7 months ago
Minimum moment Steiner trees
For a rectilinear Steiner tree T with a root, define its k-th moment Mk(T) = T (dT (u))k du, where the integration is over all edges of T, dT (u) is the length of the unique path ...
Wangqi Qiu, Weiping Shi