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» The Kernel Least-Mean-Square Algorithm
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CIKM
2009
Springer
15 years 10 months ago
Learning to rank graphs for online similar graph search
Many applications in structure matching require the ability to search for graphs that are similar to a query graph, i.e., similarity graph queries. Prior works, especially in chem...
Bingjun Sun, Prasenjit Mitra, C. Lee Giles
137
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EMMCVPR
2007
Springer
15 years 10 months ago
3D Computation of Gray Level Co-occurrence in Hyperspectral Image Cubes
This study extended the computation of GLCM (gray level co-occurrence matrix) to a three-dimensional form. The objective was to treat hyperspectral image cubes as volumetric data s...
Fuan Tsai, Chun-Kai Chang, Jian-Yeo Rau, Tang-Huan...
135
Voted
MLDM
2007
Springer
15 years 10 months ago
Nonlinear Feature Selection by Relevance Feature Vector Machine
Support vector machine (SVM) has received much attention in feature selection recently because of its ability to incorporate kernels to discover nonlinear dependencies between feat...
Haibin Cheng, Haifeng Chen, Guofei Jiang, Kenji Yo...
FCSC
2007
159views more  FCSC 2007»
15 years 3 months ago
Ranking with uncertain labels and its applications
1 The techniques for image analysis and classi cation generally consider the image sample labels xed and without uncertainties. The rank regression problem is studied in this pape...
Shuicheng Yan, Huan Wang, Jianzhuang Liu, Xiaoou T...
116
Voted
SIGIR
2008
ACM
15 years 3 months ago
Learning to rank with partially-labeled data
Ranking algorithms, whose goal is to appropriately order a set of objects/documents, are an important component of information retrieval systems. Previous work on ranking algorith...
Kevin Duh, Katrin Kirchhoff