Minimum spanning tree - Wikipedia
A planar graph and its minimum spanning tree. Each edge is labeled with its weight, which here is roughly proportional to its length. A minimum spanning tree (MST) or minimum weight spanning tree is a subset of the edges of a connected, edge-weighted undirected graph that connects all the vertices together, without any cycles and with the minimum possible total edge weight.[1] That is, it is a spa
ICML 2009 tutorial: Modeling Social and Information Networks: Opportunities for ML
Who should attend: Since network data arises in so many different areas of data mining and machine learning, this tutorial should be of theoretical and practical interest to a large part of the machine learning community. The tutorial will not require prior knowledge beyond the basic concepts covered in introductory machine learning and algorithms classes. Presenter: Jure Leskovec is an assistant
NIPS 2008 Proceedings
Advances in Neural Information Processing Systems 21 (NIPS 2008) The papers below appear in Advances in Neural Information Processing Systems 21 edited by D. Koller and D. Schuurmans and Y. Bengio and L. Bottou. They are proceedings from the conference, "Neural Information Processing Systems 2008." Structure Learning in Human Sequential Decision-Making Daniel Acuna, Paul R. Schrater The Gaussian P
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gboost - Graph Boosting Toolbox for Matlab
The gboost toolbox is a framework for classification of connected, undirected, labeled graphs. A typical graph is shown on the right: each node and edge is labeled by a discrete value. The gboost classifiers check for the presence of certain subgraphs in the larger graph. The subgraphs being checked are optimally determined by discriminative subgraph mining. The classification hypotheses is interp
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