참고문헌
- Ai, X. W., Hu, T., Li, X. and Xiong, H. (2010). Clustering high-frequency stock data for trading volatility analysis, In Proceedings of 9th International Conference on Machine Learning and Applications (ICMLA), Washington, DC, 333-338.
- Asgharbeygi, N. and Maleki, A. (2008). Geodesic k-means clustering, In Proceedings of 19th International Conference on Pattern Recognition (ICPR 2008), Tampa, FL, 1-4.
- Bhattacharya, R. and Patrangenaru, V. (2003). Large sample theory of intrinsic and extrinsic sample means on manifolds. I, Annals of Statistics, 31, 1-29. https://doi.org/10.1214/aos/1046294456
- Cachier, P., Pennec, X. and Ayache, N. (1999). Fast non rigid matching by gradient descent: Study and improvements of the "demons" algorithm, RR-3706, Available from: https://hal.inria.fr/inria-00072962/
- Fletcher, P. T. and Joshi, S. (2004). Principal geodesic analysis on symmetric spaces: Statistics of diffusion tensors. In M. Sonka, et al. (Eds.), Computer Vision and Mathematical Methods in Medical and Biomedical Image Analysis, Springer, Heidelberg, 87-98.
- Goh, A. and Vidal, R. (2008). Clustering and dimensionality reduction on Riemannian manifolds, In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR2008), Anchorage, AK, 1-7.
- Hartigan, J. A. andWong, M. A. (1979). Algorithm AS 136: A k-means clustering algorithm, Journal of the Royal Statistical Society Series C (Applied Statistics), 28, 100-108.
- Jayasumana, S., Hartley, R., Salzmann, M., Li, H., and Harandi, M. (2013). Kernel methods on the Riemannian manifold of symmetric positive definite matrices, In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR2013), Portland, OR, 73-80.
- Kim, J., Shim, K. H. and Choi, S. (2007). Soft geodesic kernel k-means, In Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP2007), Honolulu, HI, 429-432.
- Schwartzman, A. (2006). Random ellipsoids and false discovery rates: Statistics for diffusion tensor imaging data (Doctoral dissertation), Stanford University, CA.
- Xu, R. and Wunsch, D. (2005). Survey of clustering algorithms, IEEE Transactions on Neural Networks, 16, 645-678. https://doi.org/10.1109/TNN.2005.845141
- Wang, Z. and Vemuri, B. C. (2005). DTI segmentation using an information theoretic tensor dissimilarity measure, IEEE Transactions on Medical Imaging, 24, 1267-1277. https://doi.org/10.1109/TMI.2005.854516