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DuSK: A Dual Structure-preserving Kernel for Supervised Tensor Learning with Applications to Neuroimages
With advances in data collection technologies, tensor data is assuming increasing prominence in many applications and the problem of supervised tensor learning has emerged as a topic of critical significance in the data mining and machine learning community. Conventional methods for supervised tenso...
Uloženo v:
| Vydáno v: | Proc SIAM Int Conf Data Min |
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| Hlavní autoři: | , , , , , |
| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
2014
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| Témata: | |
| On-line přístup: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4410984/ https://ncbi.nlm.nih.gov/pubmed/25927014 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1137/1.9781611973440.15 |
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