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KDD
2010
ACM
272views Data Mining» more  KDD 2010»
13 years 7 months ago
Scalable similarity search with optimized kernel hashing
Scalable similarity search is the core of many large scale learning or data mining applications. Recently, many research results demonstrate that one promising approach is creatin...
Junfeng He, Wei Liu, Shih-Fu Chang
PAMI
2010
168views more  PAMI 2010»
13 years 7 months ago
Surface-from-Gradients without Discrete Integrability Enforcement: A Gaussian Kernel Approach
—Representative surface reconstruction algorithms taking a gradient field as input enforces the integrability constraint in a discrete manner. While enforcing integrability allo...
Heung-Sun Ng, Tai-Pang Wu, Chi-Keung Tang
ADCM
2008
136views more  ADCM 2008»
13 years 9 months ago
Learning and approximation by Gaussians on Riemannian manifolds
Learning function relations or understanding structures of data lying in manifolds embedded in huge dimensional Euclidean spaces is an important topic in learning theory. In this ...
Gui-Bo Ye, Ding-Xuan Zhou
DASFAA
2003
IEEE
151views Database» more  DASFAA 2003»
14 years 2 months ago
Approximate String Matching in DNA Sequences
Approximate string matching on large DNA sequences data is very important in bioinformatics. Some studies have shown that suffix tree is an efficient data structure for approxim...
Lok-Lam Cheng, David Wai-Lok Cheung, Siu-Ming Yiu
IPL
1998
119views more  IPL 1998»
13 years 8 months ago
A 2.5-Factor Approximation Algorithm for the k-MST Problem
The k-MST problem requires finding that subset of at least k vertices of a given graph whose Minimum Spanning Tree has least weight amongst all subsets of at least k vertices. Th...
Sunil Arya, H. Ramesh