核函数的计算机,一种高效的分布式树核函数分类算法

[1] HASHIMOTO K, TAKIGAWA I, SHIGA M, et al. Mining significant tree patterns in carbohydrate sugar chains[J] . Bioinformatics, 2008, 24(2)：167-173.

[2] DSSEL P, GEHL C, LASKOV P, et al. Incorporation of application layer protocol syntax into anomaly detection[C] //Information Systems Security. Berlin：Springer, 2008：188-202.

[3] MacCARTNEY B, GRENAGER T, De MARNEFFE M C, et al. Learning to recognize features of valid textual entailments[C] //Proc of the North American Conference on Human Language Technology. 2006：41-48.

[4] COLLINS M, DUFFY N. Convolution kernels for natural language[C] //Proc of NIPS. 2001：625-632.

[5] SHIN K, CUTURI M, KUBOYAMA T. Mapping kernels for trees[C] //Proc of the 25th International Conference on Machine Learning. 2008：961-968.

[6] 胡正平, 冯凯. 高维空间多分辨率最小生成树模型的自适应一类分类算法[J] . 自动化学报, 2012, 38(5)：110-118.

[7] RIECK K, KRUEGER T, BREFELD U, et al. Approximate tree kernels[J] . Journal of Machine Learning Research, 2010, 11(2)：555-580.

[8] PIGHIN D, MOSCHITTI A. On reverse feature engineering of syntactic tree kernels[C] //Proc of the 14th Conference on Computational Natural Languages Learning. 2010：223-233.

[9] 数据集网站[EB/OL] . http：//l2r. cs. uiuc. edu/cogcomp/Data/QA/QC/.

[10] DAGAN I, GLICKMAN O, MAGNINI B. The PASCAL recognising textual entailment challenge[C] //Proc of the 1st PASCAL Machine Learning Challenges Workshop. Berlin：Springer, 2006：177-190.