Computer Science ›› 2017, Vol. 44 ›› Issue (Z11): 106-109.doi: 10.11896/j.issn.1002-137X.2017.11A.021
Previous Articles Next Articles
TANG Yan-qin, PAN Zhi-song and ZHANG Yan-yan
[1] BIELZA C,LI G,LARRANAGA P.Multi-dimensional classification with Bayesian networks[J].International Journal of Approximate Reasoning,2011,52:705-727. [2] TIBSHIRANI R.Regression shrinkage and selection via the lasso[J].Journal of the Royal Statistical Society,2011,73(3):267-288. [3] ZHOU J,CHEN J,YE J.MALSAR:Multi-tAsk Learning viaStructurAl Regularization[D].Arizona State University,2012. [4] 肖瑞.不确定性时间序列的降维与相似性匹配研究[D].上海:东华大学,2014. [5] 王琼瑶.基于改进的支持向量机技术在股票短期价格预测中的应用[D].重庆:重庆交通大学,2015. [6] NG A.Stanford Engineering Everywhere CS229 lecture-MachineLearning.https://see.stanford.edu/course/cs229. [7] MURPHY K P.Machine Learning:A Probabilistic Perspective[M].MIT Press,2012. [8] BECK A,TEBOULLE M.A fast iterative shrinkage-thresholding algorithm for linear inverse problems[J].Siam Journal on Imaging Sciences,2009,2(1):183-202. [9] HAN L,ZHANG Y.Multi-stage multi-task learning with re-duced rank[C]∥Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence(AAAI-16).2016. [10] LEE G,YANG E,HWANG S J.Asymmetric multi-task learning based on task relatedness and loss[C]∥Proceedings of the 33rd International Conference on Machine Learning.New York,NY,USA,2016 :230-238. [11] 吴喜之,刘苗编.应用时间序列分析:R软件陪同[M].北京:机械工业出版社,2014. [12] TASKAR B.Learning structured prediction models:A large marginapproach[D].Stanford University,2004. [13] JOACHIMS T,HOFMANN T,YUE Y S,et al.Predicting Struc-tured Objects with Support Vector Machines[J].Communications of the ACM,2009,52(11):97-104. [14] JOACHIMS T,FINLEY T,YU C N J.Cutting-plane training of structural svms[J].Machine Learning,2009,77(1):27-59. [15] HAGAN M T,DEMUTH HB,BEALE M H,et al.Neural network design[M].PWS Publishing Company Boston,1996. [16] MAGERMAN D M.Statistical decision-tree models for parsing[C]∥Proceedings of the 33rd Annual Meeting on Association for Computational Linguistics.1995:276-283. [17] DINUZZO F,ONG C S,GEHLER P,et al.Learning output kernels with block coordinate descent[C]∥Proceedings of the 28th Annual International Conference on Machine Learning.Bellevue,WA,USA,2011. [18] DINUZZO F,FUKUMIZU K.Learning low-rank output kernels[J].Journal of Machine Learning Research Proceedings Track ,2011(20):181-196. [19] ZHANG M L,ZHOU Z H.A Review on Multi-Label Learning Algorithms[J].IEEE Transactions on Knowledge & Data Engineering,2014,6(8):1819-1837. |
No related articles found! |
|