This book constitutes the thoroughly refereed post-proceedings
of the International Workshop on Statistical Network Analysis:
Models, Issues, and New Directions held in Pittsburgh, PA, USA in
June 2006 as associated event of the 23th International Conference
on Machine Learning, ICML 2006.
The 12 revised full papers and 4 invited lectures presented
together with the summary of the closing panel discussion were
carefully revised and selected during two rounds of reviewing and
improvement from the presentations at the workshop. The papers
focus on probabilistic methods for network analysis, paying special
attention to model design and computational issues of learning and
inference. The workshop brings together statistical network
modeling researchers from different communities to create and
motivate novel modeling approaches, diverse applications, and new
research directions.
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