Learning from networked examples

11 May 2014Yuyi WangJan RamonZheng-Chu Guo

Many machine learning algorithms are based on the assumption that training examples are drawn independently. However, this assumption does not hold anymore when learning from a networked sample because two or more training examples may share some common objects, and hence share the features of these shared objects... (read more)

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