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108
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JCDCG
2004
Springer
15 years 8 months ago
Farthest-Point Queries with Geometric and Combinatorial Constraints
In this paper we discuss farthest-point problems in which a set or sequence S of n points in the plane is given in advance and can be preprocessed to answer various queries efficie...
Ovidiu Daescu, Ningfang Mi, Chan-Su Shin, Alexande...
117
Voted
NIPS
2008
15 years 4 months ago
Kernel Measures of Independence for non-iid Data
Many machine learning algorithms can be formulated in the framework of statistical independence such as the Hilbert Schmidt Independence Criterion. In this paper, we extend this c...
Xinhua Zhang, Le Song, Arthur Gretton, Alex J. Smo...
124
Voted
CVPR
2007
IEEE
16 years 4 months ago
Integrating Global and Local Structures: A Least Squares Framework for Dimensionality Reduction
Linear Discriminant Analysis (LDA) is a popular statistical approach for dimensionality reduction. LDA captures the global geometric structure of the data by simultaneously maximi...
Jianhui Chen, Jieping Ye, Qi Li
99
Voted
PR
2006
107views more  PR 2006»
15 years 2 months ago
Pyramid segmentation algorithms revisited
The main goal of this work is to compare pyramidal structures proposed to solve segmentation tasks. Segmentation algorithms based on regular and irregular pyramids are described, ...
Rebeca Marfil, Luis Molina-Tanco, Antonio Bandera,...
121
Voted
PAKDD
2005
ACM
96views Data Mining» more  PAKDD 2005»
15 years 8 months ago
Kernels over Relational Algebra Structures
Abstract. In this paper we present a novel and general framework based on concepts of relational algebra for kernel-based learning over relational schema. We exploit the notion of ...
Adam Woznica, Alexandros Kalousis, Melanie Hilario