佟宏志 教 授

xingming  tonghongzhi      

zhuanye  tongji               

xibie  shujukexuexi

zhicheng  chuanshou        

bangongdelvfeng 64497289    

dianziyoujian tonghz@bikinisbarandgrill.com

 

 

jiaodaobeijing:

1992nian9yuezhi1996nian7yuehebeishifandaxueshuxuexi,lixuexueshi;

1996nian9yuezhi1999nian7yuehebeishifandaxueshuxinxueyuan,lixueshuoshi;

2004nian9yuezhi2008nian7yuebeijingdaxueshuxuekexuexueyuan,lixueboshi

 

renwulvli:

2008nian7yuezhijin,ruidian1fencaipingtai ;

1999nian7yuezhi2004nian9yue,hebeishifandaxueshuxinxueyuan

 

chuanshoukecheng: gaodangshuxue,shuxuechanfa,jilvyushulitongji,xianxingdaishu

yantaofanchou: tongjijinxiushiji,jixiejinxiujiqiliyong,shujufajueyujijiao

 

shouyaoyantaogongxiao:

[1] h .z. tong, a note on support vector machines with polynomial kernels, neural computation, 28, 2016. (sci)

[2] h. z. tong, d. r. chen and f. h yang, classification with polynomial kernels and l1-coefficient regularization, taiwanese journal of mathematics, 18(5), 1633-1651, 2014. (sci)

[3] h. z. tong, d. r. chen and f. h yang, a simpler approach to coefficient regularized support vector machines regression, abstract and applied analysis, volume 2014, article id 206015, 8 pages, 2014. (sci)

[4] h. z. tong, d. r. chen and f. h yang, learning with convex loss and indefinite kernels, neural computation, 26, 158-3184, 2014. (sci)

[5] h. z. tong, d. r. chen and f. h yang, learning rates for l1-regularized kernel classifiers, journal of applied mathematics, volume 2013, article id 496282, 11 pages, 2013. (sci)

[6] h. z. tong, d. r. chen and f. h yang, support vector machines regression with l1- regularizer, journal of approximation theory, 164, 1331-1344, 2012. (sci)

[7] tonghongzhi ,chendirong,yangfenghong,zhengzehuahuiguisuanfadejisujinxiulv,zhongguokexue: shuxue,di42juan,di12qi,1251-1262ye,2012.

[8] h. z. tong, d. r. chen and f. h yang, least square regression with lp-coefficient regularization, neural computation, 22, 3221-3235, 2010. (sci)

[9] h. z. tong, d. r. chen and l. z. peng, analysis of support vector machines regression, foundation of computational mathematics, 9, 243-257, 2009. (sci)

[10] h. z. tong, d. r. chen and l. z. peng, learning rates for regularized classifiers using multivariate polynomial kernels, journal of complexity, 24, 619-631,2008 . (sci)


 

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