October 8, 2014 · 6:30 PM
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Want to get your feet wet with graph algorithms? There's an excellent paper by Newman on modularity optimization. It's a graph clustering algorithm that tries to optimize "modularity" (the division of the graph into communities) by looking at eigenvectors of a matrix. You'll need some basic understanding of eigenvectors in linear algebra for this one, but that's about it as far as prerequisites go! This paper is really well written, and I think you'll find it inspiring. Here's the link:
We'll set the date and location once a few people comment saying they've read the paper, and/or are ready to discuss it. Don't expect to understand everything after a first read through! Math is hard. That's what the group is here for.
• Linear Algebra: (intermediate level) matrix multiplication; eigenvectors and eigenvalues of matrices
• Graph Theory: (beginner level) know what a graph is; understand (or want to understand!) why we might want to cluster the nodes of a graph.
• Computer Science: (beginner level) know what an algorithm is. optional: Understand why it is important that an algorithm runs quickly; Understand what a heuristic is.