Qian Peng-Jiang, Wang Shi-Tong, Deng Zhao-Hong, Xu Hua. Fast spectral clustering for large data sets using minimal enclosing ball. Acta Electronica Sinica, 2010, 38(9): 2035-2041(钱鹏江, 王士同, 邓赵红, 徐华. 基于最小包含球的大数据集快速谱聚类算法. 电子学报, 2010, 38(9): 2035-2041)
[2]
Tsang I, Kwok J, Zurada J. Generalized core vector machines. IEEE Transactions on Neural Networks, 2006, 17(5): 1126-1140
[3]
Badoiu M, Har-Peled S, Indyk P. Approximate clustering via core-sets. In: Proceedings of the 34th Annual ACM Symposium on Theory of Computing. Quebec, Canada: ACM, 2002. 250-257
[4]
Xu D X. Energy, Entropy and Information Potential for Neural Computation [Ph.D. dissertation], University of Florida, USA, 1998
[5]
Qian Peng-Jiang, Wang Shi-Tong, Deng Zhao-Hong. Fast adaptive similarity-based clustering using sparse Parzen window density estimation. Acta Automatica Sinica, 2011, 37(2): 179-187(钱鹏江, 王士同, 邓赵红. 基于稀疏Parzen窗密度估计的快速自适应相似度聚类方法. 自动化学报, 2011, 37(2): 179-187)
[6]
Chen S, Hong X, Harris C J. Probability density estimation with tunable kernels using orthogonal forward regression. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 2010, 40(4): 1101-1114
[7]
Jeon B, Landgrebe D A. Fast Parzen density estimation using clustering-based branch and bound. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1994, 16(9): 950-954
[8]
Freedman D, Kisilev P. Fast data reduction via KDE approximation. In: Proceedings of the Data Compression Conference. Utah, USA: IEEE, 2009. 445-445
[9]
Steele J M. The Cauchy Schwarz Master Class: an Introduction to the Art of Mathematical Inequalities. New York: Cambridge University Press, 2004. 99-102
[10]
Chen P H, Fan R E, Lin C J. A study on SMO-type decomposition methods for support vector machines. IEEE Transactions on Neural Networks, 2006, 17(4): 893-908
[11]
Lee C, Zaiane O, Park H, Huang J, Greiner R. Clustering high dimensional data: a graph-based relaxed optimization approach. Information Sciences, 2008, 178(23): 4501-4511
[12]
Deng Z H, Chung F L, Wang S T. FRSDE: fast reduced set density estimator using minimal enclosing ball approximation. Pattern Recognition, 2008, 41(4): 1363-1372
[13]
Badoiu M, Clarkson K L. Optimal core-sets for balls. Computational Geometry: Theory and Applications, 2008, 40(1): 14-22
[14]
Tsang I, Kwok J, Cheung P. Core vector machines: fast SVM training on very large data sets. The Journal of Machine Learning Research, 2005, 6: 363-392
[15]
Maynou J, Gallardo-Chacon J J, Vallverdu M, Caminal P, Perera A. Computational detection of transcription factor binding sites through differential Renyi entropy. IEEE Transactions on Information Theory, 2010, 56(2): 734-741
[16]
Jenssen R. Kernel entropy component analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010, 32(5): 847-860
[17]
Zeng X, Durrani T S. Estimation of mutual information using copula density function. Electronics Letters, 2011, 47(8): 493-494
[18]
Girolami M, He C. Probability density estimation from optimally condensed data samples. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2003, 25(10): 1253-1264
[19]
Heiler M, Keuchel J, Schnorr C. Semidefinite clustering for image segmentation with a-priori knowledge. In: Proceedings of the 27th Symposium of the German Association for Pattern Recognition. Vienna, Austria: Springer, 2005. 309-317
[20]
Yang M S, Wu K L. A similarity-based robust clustering method. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004, 26(4): 434-448
[21]
Fan R E, Chen P H, Lin C J. Working set selection using second order information for training support vector machines. The Journal of Machine Learning Research, 2005, 6: 1889-1918
