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VLDB
2000
ACM
114views Database» more  VLDB 2000»
14 years 1 months ago
The A-tree: An Index Structure for High-Dimensional Spaces Using Relative Approximation
We propose a novel index structure, A-tree (Approximation tree), for similarity search of high-dimensional data. The basic idea of the
Yasushi Sakurai, Masatoshi Yoshikawa, Shunsuke Uem...
AIM
2011
13 years 1 months ago
Transfer Learning by Reusing Structured Knowledge
Transfer learning aims to solve new learning problems by extracting and making use of the common knowledge found in related domains. A key element of transfer learning is to ident...
Qiang Yang, Vincent Wenchen Zheng, Bin Li, Hankz H...
3DPVT
2006
IEEE
188views Visualization» more  3DPVT 2006»
14 years 1 months ago
Statistical Inference of Biological Structure and Point Spread Functions in 3D Microscopy
We present a novel method for detecting and quantifying 3D structure in stacks of microscopic images captured at incremental focal lengths. We express the image data as stochastic...
Joseph Schlecht, Kobus Barnard, Barry Pryor
CORR
2007
Springer
140views Education» more  CORR 2007»
13 years 10 months ago
From the entropy to the statistical structure of spike trains
— We use statistical estimates of the entropy rate of spike train data in order to make inferences about the underlying structure of the spike train itself. We first examine a n...
Yun Gao, Ioannis Kontoyiannis, Elie Bienenstock
CVPR
2010
IEEE
13 years 8 months ago
P-N learning: Bootstrapping binary classifiers by structural constraints
This paper shows that the performance of a binary classifier can be significantly improved by the processing of structured unlabeled data, i.e. data are structured if knowing the ...
Zdenek Kalal, Jiri Matas, Krystian Mikolajczyk