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» Approximation Algorithms for Data Placement Problems
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SDM
2007
SIAM
145views Data Mining» more  SDM 2007»
15 years 3 months ago
Finding Motifs in a Database of Shapes
The problem of efficiently finding images that are similar to a target image has attracted much attention in the image processing community and is rightly considered an informatio...
Xiaopeng Xi, Eamonn J. Keogh, Li Wei, Agenor Mafra...
121
Voted
AAAI
2010
15 years 3 months ago
Cost-Sensitive Semi-Supervised Support Vector Machine
In this paper, we study cost-sensitive semi-supervised learning where many of the training examples are unlabeled and different misclassification errors are associated with unequa...
Yu-Feng Li, James T. Kwok, Zhi-Hua Zhou
KSEM
2009
Springer
15 years 8 months ago
A Competitive Learning Approach to Instance Selection for Support Vector Machines
Abstract. Support Vector Machines (SVM) have been applied successfully in a wide variety of fields in the last decade. The SVM problem is formulated as a convex objective function...
Mario Zechner, Michael Granitzer
SIGIR
1998
ACM
15 years 6 months ago
Fast Searching on Compressed Text Allowing Errors
Abstract We present a fast compression and decompression scheme for natural language texts that allows e cient and exible string matching by searching the compressed text directly....
Edleno Silva de Moura, Gonzalo Navarro, Nivio Zivi...
113
Voted
ICPR
2004
IEEE
16 years 3 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