Abstract
One of the key strengths of the proposed approach is that it does not require hand-tuning of model parameters but actually learns them as part of the optimization process. The learned parameters may be suitable candidates for future investigation of their role in distinguishing health and disease.
References
Surampudi S G, Naik S, Shrama A, et al. Combining Multiscale Diffusion Kernels for Learning the Structural and Functional Brain Connectivity[J]. NIPS 2016: 078766.
PreviewTips
Download
To download attachments, please log in.
Last Modified: 2017/04/06 15:35 | Author: Wen Hongwei