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Social Network Analysis | Coursera.org
M.A. in International Relations, Security, and Strategy
Introduction to Conditional Random Fields
Imagine you have a sequence of snapshots from a day in Justin Bieber’s life, and you want to label each image with the activity it represents (eating, sleeping, driving, etc.). How can you do this? One way is to ignore the sequential nature of the snapshots, and build a per-image classifier. For example, given a month’s worth of labeled snapshots, you might learn that dark images taken at 6am tend
Large graph mining: patterns, tools and case studies
Large graph mining: patterns, tools and case studies Tutorial proposal for CIKM 2008, Napa Valley, California Christos Faloutsos and Hanghang Tong, Carnegie Mellon University Abstract How do graphs look like? How do they evolve over time? How can we find patterns, anomalies and regularities in them? How to find influential nodes in the network? We will present both theoretical results and algorith
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MLG 2020 - 16th International Workshop on Mining and Learning with Graphs
Chicisimo’s Social Fashion Graph | Chicisimo
