1 |
Bordes, A., Bottou, L. and Gallinari, P. (2008). SGD-QN: Careful quasi-Newton stochastic gradient descent. Journal of Machine Learning Research, 10, 1737-1754.
|
2 |
Bottou, L. and Bousquet, O. (2008). The tradeoffs of large scale learning. In Advances in Neural Information Processing Systems, 20, 161-168.
|
3 |
Boyd, S., Parikh, N., Chu, E., Peleato, B. and Eckstein, J. (2010). Distributed optimization and statistical learning via the alternating direction method of multipliers. Foundations and Trendsr in Machine Learning, 3, 1-122.
DOI
|
4 |
Cortes, C. and Vapnik, V. (1995). Support vector networks. Machine Learning, 20, 273-297.
|
5 |
Duchi, J. and Singer, Y. (2009). Efficient online and batch learning using forward-backward splitting. Journal of Machine Learning Research, 10, 2873-2898.
|
6 |
Fan, R.-E., Chen, P.-H. and Lin, C.-J. (2005). Working set selection using second order information for training SVM. Journal of Machine Learning Research, 6, 1889-1918.
|
7 |
Forero, P. A., Cano, A. and Giannakis, G. B. (2010). Consensus-based distributed support vector machines. Journal of Machine Learning Research, 11, 1663-1707.
|
8 |
Franc, V. and Sonnenburg, S. (2008). Optimized cutting plane algorithm for support vector machines. In Proceedings of the 25th International Conference on Machine Learning, ACM, 320-327.
|
9 |
Hsieh, C.-J., and Chang, K.-W., Lin, C.-J., Keerthi, S. S and Sundararajan, S. (2008). A dual coordinate descent method for large-scale linear SVM. In Proceedings of the 25th International Conference on Machine Learning, ACM, 408-415.
|
10 |
Park, C., Kim, Y., Kim, J., Song, J. and Choi, H. (2013). Data mining using R, 2nd Edition, Kyowoo Publisher, Seoul.
|
11 |
Park, D.-J., Yun, Y.-B. and Yoon, M. (2012). Prediction of bankruptcy data using machine learning techniques. Journal of the Korean Data & Information Science Society, 23, 569-577.
과학기술학회마을
DOI
ScienceOn
|
12 |
Park, H.-J. (2011). Online abnormal events detection with online support vector machine. Journal of the Korean Data & Information Science Society, 22, 197-206.
과학기술학회마을
|
13 |
Pi, S.-Y., Park, H.-J. and Ryu, K.-H. (2011) An analysis of satisfaction index on computer education of university using kernel machine. Journal of the Korean Data & Information Science Society, 22, 921-929.
과학기술학회마을
|
14 |
Platt, J. C. (1999). Fast training of support vector machines using sequential minimal optimization. In Advances in Kernal Methods - Support Vector Learning, MIT Press, 185-208.
|
15 |
Shalev-Shwartz, S., Singer, Y., Srebro, N. and Cotter, A. (2011). Pegasos: Primal estimated sub-gradient solver for SVM. Mathematical Programming B, 127, 3-30.
DOI
|
16 |
Smola, A. J., Vishwanathan, S. V. N. and Le, Q. V. (2007). Bundle methods for machine learning. In Advances in Neural Information Processing Systems, 20, MIT Press, 1377-1384.
|
17 |
Zou, H. and Hastie, T. (2005). Regularization and variable selection via the elastic net. Journal of the Royal Statistical Society B, 67, 301-320.
DOI
ScienceOn
|