开课单位--伯明翰大学
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Partial 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:47

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Temporal 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:70

3
An 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:36

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Fast 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:41

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Robust 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:33

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Partial 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:63

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Compressed 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:51

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Multiple 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:30
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