图 书 馆开课单位--伯明翰大学
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1Partial cubes and other l1-graphs[部分立方体与其它l1图]
Sergey Shpectorov(伯明翰大学) Partial cubes are isometric subgraphs of the hypercube graphs, while l1-graphs are graphs embeddable in a hypercube up to a scale. These two classes o...
热度：67
Sergey Shpectorov(伯明翰大学) Partial cubes are isometric subgraphs of the hypercube graphs, while l1-graphs are graphs embeddable in a hypercube up to a scale. These two classes o...
热度：67
2Temporal Graphs for Dynamic Network Analysis[时序图的动态网络分析]
Mirco Musolesi(伯明翰大学) Problem: existing metrics do not capture the inherent dynamism of networks over time. We need new temporal metrics defined over temporal graphs for...
热度：89
Mirco Musolesi(伯明翰大学) Problem: existing metrics do not capture the inherent dynamism of networks over time. We need new temporal metrics defined over temporal graphs for...
热度：89
3An Exchanging-based Refinement to Sparse Gaussian Process Regression[稀疏高斯过程回归的交换细化]
Ping Sun(伯明翰大学) We propose a backward deletion procedure to Sparse Gaussian Process Regression (SGPR) model, which can be used to refine a number of se- quential forw...
热度：63
Ping Sun(伯明翰大学) We propose a backward deletion procedure to Sparse Gaussian Process Regression (SGPR) model, which can be used to refine a number of se- quential forw...
热度：63
4Fast optimization for L1 Regularization: Evaluation and Two New Approaches[L1正规化的快速优化：评估和两种新方法的介绍]
Romer Rosales(伯明翰大学) L1正规化的快速优化：评估和两种新方法介绍
热度：57
Romer Rosales(伯明翰大学) L1正规化的快速优化：评估和两种新方法介绍
热度：57
5Robust Visual Mining of Data with Error Information[具有错误信息的数据的可视化挖掘]
Jianyong Sun(伯明翰大学) 具有错误信息的数据的可视化挖掘
热度：47
Jianyong Sun(伯明翰大学) 具有错误信息的数据的可视化挖掘
热度：47
6Partial cubes and other l1-graphs[部分立方体和其他l1图]
Sergey Shpectorov(伯明翰大学) Partial cubes are isometric subgraphs of the hypercube graphs, while l1-graphs are graphs embeddable in a hypercube up to a scale. These two classes ...
热度：74
Sergey Shpectorov(伯明翰大学) Partial cubes are isometric subgraphs of the hypercube graphs, while l1-graphs are graphs embeddable in a hypercube up to a scale. These two classes ...
热度：74
7Compressed Fisher Linear Discriminant Analysis: Classification of Randomly Projected Data[压缩Fisher线性判别分析：随机投影数据的分类]
Robert J. Durrant(伯明翰大学 ) We consider random projections in conjunction with classification, specifically the analysis of Fisher's Linear Discriminant (FLD) classifier in rando...
热度：66
Robert J. Durrant(伯明翰大学 ) We consider random projections in conjunction with classification, specifically the analysis of Fisher's Linear Discriminant (FLD) classifier in rando...
热度：66
8Multiple Manifold Learning Framework based on Hierarchical Mixture Density Model[基于层次混合密度模型的多流形学习框架]
Peter Tino, Xiaoxia Wang, Mark A. Fardal(伯明翰大学) Several manifold learning techniques have been developed to learn, given a data, a single lower dimensional manifold providing a compact representatio...
热度：48
Peter Tino, Xiaoxia Wang, Mark A. Fardal(伯明翰大学) Several manifold learning techniques have been developed to learn, given a data, a single lower dimensional manifold providing a compact representatio...
热度：48
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