图 书 馆开课单位--新加坡国立大学
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11Government Perspectives on Engineering Systems[工程系统的政府观点]
Granger Morgan;Pao Chuen Lui;Mortimer Downey;Mary Good;Joseph Bordogna(新加坡国立大学) Panelists share their diverse experiences, enthusiasm, and occasional frustrations involving complex, government-based engineering projects. Mortimer ...
热度：26
Granger Morgan;Pao Chuen Lui;Mortimer Downey;Mary Good;Joseph Bordogna(新加坡国立大学) Panelists share their diverse experiences, enthusiasm, and occasional frustrations involving complex, government-based engineering projects. Mortimer ...
热度：26
12Classification of Software Behaviors for Failure Detection: A Discriminative Pattern Mining Approach[用于故障检测的软件行为分类：一种判别模式挖掘方法]
David Lo(新加坡国立大学) Software is a ubiquitous component of our daily life. We often depend on the correct working of software systems. Due to the difficulty and complexity...
热度：41
David Lo(新加坡国立大学) Software is a ubiquitous component of our daily life. We often depend on the correct working of software systems. Due to the difficulty and complexity...
热度：41
13Dynamic Captioning: Video Accessibility Enhancement for Hearing Impairment[动态字幕：听力障碍的视频辅助功能增强]
Richang Hong(新加坡国立大学) There are more than 66 million people su®ering from hear- ing impairment and this disability brings them di±culty in video content understa...
热度：83
Richang Hong(新加坡国立大学) There are more than 66 million people su®ering from hear- ing impairment and this disability brings them di±culty in video content understa...
热度：83
14Feature Selection for Support Vector Regression Using Probabilistic Prediction[基于概率预测的支持向量回归机特征选择]
Jian-Bo Yang(新加坡国立大学) This paper presents a novel wrapper-based feature selection method for Support Vector Regression (SVR) using its probabilistic predictions. The method...
热度：24
Jian-Bo Yang(新加坡国立大学) This paper presents a novel wrapper-based feature selection method for Support Vector Regression (SVR) using its probabilistic predictions. The method...
热度：24
15Robustness and Regularization of Support Vector Machines[支持向量机的鲁棒性与正则化 ]
Huan Xu(新加坡国立大学 ) We consider a robust classification problem and show that standard regularized SVM is a special case of our formulation, providing an explicit link b...
热度：34
Huan Xu(新加坡国立大学 ) We consider a robust classification problem and show that standard regularized SVM is a special case of our formulation, providing an explicit link b...
热度：34
16Sparse Algorithms are Not Stable: A No-free-lunch Theorem[稀疏算法不稳定：一个没有免费午餐的定理 ]
Huan Xu(新加坡国立大学 ) We consider two widely used notions in machine learning, namely: sparsity and stability. Both notions are deemed desirable, and are believed to lead t...
热度：28
Huan Xu(新加坡国立大学 ) We consider two widely used notions in machine learning, namely: sparsity and stability. Both notions are deemed desirable, and are believed to lead t...
热度：28
17Enhancing Semantic Web Services with Inheritance[通过继承增强语义Web服务]
Yuzhang Feng(新加坡国立大学) Currently proposed Semantic Web Services technologies allow the creation of ontology-based semantic annotations of Web services so that software agent...
热度：34
Yuzhang Feng(新加坡国立大学) Currently proposed Semantic Web Services technologies allow the creation of ontology-based semantic annotations of Web services so that software agent...
热度：34
18Estimating Local Optimums in EM Algorithm over Gaussian Mixture Model[用高斯混合模型估计EM算法的局部最优值]
Zhenjie Zhang(新加坡国立大学) EM algorithm is a very popular method to estimate the parameters of Gaussian Mixture Model from a large observation set. However, in most cases, EM al...
热度：71
Zhenjie Zhang(新加坡国立大学) EM algorithm is a very popular method to estimate the parameters of Gaussian Mixture Model from a large observation set. However, in most cases, EM al...
热度：71