Open Access
MATEC Web of Conferences
Volume 56, 2016
2016 8th International Conference on Computer and Automation Engineering (ICCAE 2016)
Article Number 01003
Number of page(s) 5
Section Computer and Information technologies
Published online 26 April 2016
  1. Schohn G, Cohn D, Less is more: Active learning with support vector machines, InterNational Conference on Machine. Learning, 839–846, (2000).
  2. Tong S, Active learning: theory and application, Stanford. University, (2001)
  3. Zhou D, Bousquet O, Lal T N, et al, Learning with local and global consistency, Advances in neural information processing systems, 16(16): 321–328, (2004)
  4. Chang C C, Lin C J, LIBSVM: A library for support vector machines, ACM TIST, 2(3): 27, (2011)
  5. Wang J, Jebara T, Chang S F, Semi-supervised learning using greedy max-cut, J. Mach. Learn. Res. (JMLR), 14(1): 771–800, (2013)
  6. Elhamifar E, Vidal R, Sparse subspace clustering: Algorithm, theory, and applications, “ IEEE Trans. Pattern. Anal. Mach. Intell. (TPAMI), 35(11): 2765–2781, (2013) [CrossRef]
  7. Wang Y, Jiang Y, Wu Y, et al, Spectral clustering on multiple manifolds, Neural. Networks, IEEE Trans. Neural.Netw., 22(7): 1149–1161, (2011) [CrossRef]