Thoracic
发表于 2025-3-21 17:55:57
书目名称Support Vector Machines Applications影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0882143<br><br> <br><br>书目名称Support Vector Machines Applications影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0882143<br><br> <br><br>书目名称Support Vector Machines Applications网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0882143<br><br> <br><br>书目名称Support Vector Machines Applications网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0882143<br><br> <br><br>书目名称Support Vector Machines Applications被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0882143<br><br> <br><br>书目名称Support Vector Machines Applications被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0882143<br><br> <br><br>书目名称Support Vector Machines Applications年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0882143<br><br> <br><br>书目名称Support Vector Machines Applications年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0882143<br><br> <br><br>书目名称Support Vector Machines Applications读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0882143<br><br> <br><br>书目名称Support Vector Machines Applications读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0882143<br><br> <br><br>
吸引力
发表于 2025-3-21 20:53:02
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canonical
发表于 2025-3-22 01:43:49
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LIMN
发表于 2025-3-22 07:41:47
Yunqian Ma,Guodong GuoFocus on current developments in the field of Support Vector Machines.Illustrates critical applications of support vector machines to important real world problems.Provides critical review of the stat
构成
发表于 2025-3-22 08:55:19
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DEMUR
发表于 2025-3-22 14:05:38
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ornithology
发表于 2025-3-22 18:25:04
Multi-Class Support Vector Machine, from . × . to . by introducing a relaxed classification error bound. The experimental discussion demonstrates that the SimMSVM approach can greatly speed up the training process, while maintaining a competitive classification accuracy.
合唱团
发表于 2025-3-22 22:55:13
Security Evaluation of Support Vector Machines in Adversarial Environments,VMs in real-world security problems. For each attack technique, we evaluate its impact and discuss whether (and how) it can be countered through an adversary-aware design of SVMs. Our experiments are easily reproducible thanks to . code that we have made available, together with all the employed datasets, on a public repository.
interference
发表于 2025-3-23 03:52:37
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Desert
发表于 2025-3-23 06:56:30
Novel Inductive and Transductive Transfer Learning Approaches Based on Support Vector Learning,tive transfer learning, domain adaptation kernelized support vector machine (DAKSVM) and its two extensions are proposed, which can reduce the distribution gap between different domains in an RKHS as much as possible by integrating the large margin learner with the proposed generalized projected maximum distribution distance (GPMDD) metric.