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ADCM
2006
74views more  ADCM 2006»
15 years 3 months ago
Linearly constrained reconstruction of functions by kernels with applications to machine learning
This paper investigates the approximation of multivariate functions from data via linear combinations of translates of a positive definite kernel from a reproducing kernel Hilbert...
Robert Schaback, J. Werner
FOCS
2006
IEEE
15 years 9 months ago
Algorithms on negatively curved spaces
d abstract] Robert Krauthgamer ∗ IBM Almaden James R. Lee † Institute for Advanced Study We initiate the study of approximate algorithms on negatively curved spaces. These spa...
Robert Krauthgamer, James R. Lee
122
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SIROCCO
2004
15 years 5 months ago
The Range Assignment Problem in Static Ad-Hoc Networks on Metric Spaces
In this paper we study the range assignment problem in static ad-hoc networks on metric spaces. We consider the h-strong connectivity and h-broadcast problems on trees, high dimens...
Deshi Ye, Hu Zhang
ICPR
2004
IEEE
16 years 4 months ago
Classification Probability Analysis of Principal Component Null Space Analysis
In a previous paper [1], we have presented a new linear classification algorithm, Principal Component Null Space Analysis (PCNSA) which is designed for problems like object recogn...
Namrata Vaswani, Rama Chellappa
VLDB
2004
ACM
127views Database» more  VLDB 2004»
16 years 4 months ago
Querying high-dimensional data in single-dimensional space
In this paper, we propose a new tunable index scheme, called iMinMax(), that maps points in highdimensional spaces to single-dimensional values determined by their maximum or minim...
Cui Yu, Stéphane Bressan, Beng Chin Ooi, Kian-Lee...