Cargando…
Ranking Support Vector Machine with Kernel Approximation
Learning to rank algorithm has become important in recent years due to its successful application in information retrieval, recommender system, and computational biology, and so forth. Ranking support vector machine (RankSVM) is one of the state-of-art ranking models and has been favorably used. Non...
Autores principales: | Chen, Kai, Li, Rongchun, Dou, Yong, Liang, Zhengfa, Lv, Qi |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5331172/ https://www.ncbi.nlm.nih.gov/pubmed/28293256 http://dx.doi.org/10.1155/2017/4629534 |
Ejemplares similares
-
Privacy Preserving RBF Kernel Support Vector Machine
por: Li, Haoran, et al.
Publicado: (2014) -
Regularization, optimization, kernels, and support vector machines
por: Suykens, Johan A K, et al.
Publicado: (2015) -
Support Vector Machines and Kernels for Computational Biology
por: Ben-Hur, Asa, et al.
Publicado: (2008) -
Local clustering via approximate heat kernel PageRank with subgraph sampling
por: Lu, Zhenqi, et al.
Publicado: (2021) -
iScore: An MPI supported software for ranking protein–protein docking models based on a random walk graph kernel and support vector machines
por: Renaud, Nicolas, et al.
Publicado: (2020)