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30篇 您的检索式：作者名="CHALIMOURDA A"

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	题名	作者	年代	出处	被引量
1	Experimentally Optimal v in Support Vector Regression for Different Noise Models and Parameter Setting显示文摘	Chalimourda Schlkopf B Smola A	2004	Neural Networks2004，17，1：	1
2	Experimentally Optimal V in Support Vector Regression for Different Noise Models and Parameter Settings显示文摘	CHALIMOURDA C SCHOLKOPF B SMOLA A	2004	Neural Networks2004，17，1：	1
3	Experimentally optimal v in support vector regression for different noise models and parameter settings显示文摘	Chalimourda A Scholkopf B Smola A	2004	Neural Net - works2004，17，：	1
4	Experimentally optimal v in support vector regression for different noise models and parameter settings显示文摘	A Chalimourda B Scholkopf A Smola	2004	Neural Networks2004，17，：	1
5	Experimentally optimal v in support vector regression for different noise models and parameter settings显示文摘	Chalimourda A Scholkopf B Smola A J	2004	Neural Networks2004，17，1：	1
6	Experimentally optimal v in support vector regressionfor different noise and parameter settings显示文摘	CHALIMOURDA A SCHOLKOPF B SMOLA A J	2004	Neural Networks2004，17，1：	1
7	Experimentally optima/v in support vector regression for different noise models and parameters settings显示文摘	CHALIMOURDA A SCHOLKOPF B SMOLA A J	2004	Neural Networks2004，17，1：	1
8	Experimentally Optimal v in Support Vector Regression for Different Noise Models and Parameter Settings显示文摘	Chalimourda A Scholkopf B Smola A J	2004	Neural Networks (S0893-6080)2004，17，1：	1
9	Experimentally optimal v in support vector regression for different noise models and parameter settings 显示文摘	Chalimourda A SchSlkopf B Smola A	2004	Neural Networks2004，17，1：	1
10	Experimentally optimal v in support vector regression for different noise models and parameters settings显示文摘	CHALIMOURDA A SCH LKOPF B SMOLA A J	2004	Neu ral Networks2004，17，1：	1
11	Experimentally optimal v in support vector regression for different noise and parameter settings 显示文摘	A Chalimourda B Scholkopf A J Smola	2005	Neural Networks (S0893-6080)2005，18，2：	1
12	Experimentally optimal v in support vector regression for different noise models and parameter settings显示文摘	Chalimourda A Seholkopf B Smola A	2004	Neural Networks2004，17，：	1
13	Experimentally optimal v in support vector regression for different noise models and parameter settings显示文摘	Chalimourda A Scholkopf B Smola A J	2004	Neural Networks2004，17，1：	1
14	Experimentally optimal v in support vector regression for different noise models and parameter setting显示文摘	CHALIMOURDA A SCHLKOPF B SMOI A A	2004	Neural Networks2004，17，1：	1
15	Experimentally optima υ in support vector regression for different noise models and parameter settings显示文摘	CHALIMOURDA A SCHOLKOPF B SMOLA A	2004	Neural Networks2004，17，1：	1
16	Experimentally optimal v in support vector regression for different noise models and parameter settings显示文摘	Chalimourda A Scholkopf B Smola A J	2004	Neural Networks2004，17，1：	1
17	Experimentally optimal v in support vector regression fordifferent noise models and parameter settings 显示文摘	CHALIMOURDA A SCHOLKOPT B SMOLA A	2004	IEEETransactions on Neural Networks2004，15，2：	1
18	Experimen-tally optimal in support vector regression for different noise models and arameter settings显示文摘	Chalimourda A Scholkopf B Smola A	2004	Neural Networks2004，17，：	1
19	Experimentally optimal υ in support vector regression for different Noise models and parameter settings显示文摘	Athanassia Chalimourda Scholkopt B Smola A	2004	IEEE Trans on Neural Networks2004，15，2：	1
20	Experimentally optimal i, in support vector regression for different noise models and parameter settings 显示文摘	Chalimourda A Sch-lkopf B Smola A J	2004	Neural Networks2004，17，1：	1

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