Network Model Selection Using Task-Focused Minimum Description Length

Networks are fundamental models for data used in practically every application domain. In most instances, several implicit or explicit choices about the network definition impact the translation of underlying data to a network representation, and the subsequent question(s) about the underlying system being represented. Users of downstream network data may not even be aware of these choices or their impacts. We propose a task-focused network model selection methodology which addresses several key challenges. Our approach constructs network models from underlying data and uses minimum description length (MDL) criteria for selection. Our methodology measures efficiency, a general and comparable measure of the network's performance of a local (i.e. node-level) predictive task of interest. Selection on efficiency favors parsimonious (e.g. sparse) models to avoid overfitting and can be applied across arbitrary tasks and representations. We show stability, sensitivity, and significance testing in our methodology

Network Model Selection for Task-Focused Attributed Network Inference

Networks are models representing relationships between entities. Often these relationships are explicitly given, or we must learn a representation which generalizes and predicts observed behavior in underlying individual data (e.g. attributes or labels). Whether given or inferred, choosing the best representation affects subsequent tasks and questions on the network. This work focuses on model selection to evaluate network representations from data, focusing on fundamental predictive tasks on networks. We present a modular methodology using general, interpretable network models, task neighborhood functions found across domains, and several criteria for robust model selection. We demonstrate our methodology on three online user activity datasets and show that network model selection for the appropriate network task vs. an alternate task increases performance by an order of magnitude in our experiments

The ornithological diaries of Helmut Sick (1910 - 1991)

On the 10th of January 2010 Helmut Sick, the German-Brazilian explorer of neotropical birds would have had his 100th anniversary. He made his PhD under supervision of Erwin Stresemann in 1937 about the structure of bird feathers. 1939 he joined a three months expedition to Brazil but was so fascinated about the bird life that he stayed much longer and in 1952 he became citizen of Brazil. Helmut Sick was director at the National Museum Boa Vista and was professor for zoology an the State University in Rio. He became member of the Academia Brasileira de Ciências und honorary citizen of Rio de Janeiro. His probably most important book were the two volumes of „Ornitologia brasiliera, uma introduÇão“, which has been revised in 1993 in an English version “Birds in Brazil. A natural history“. Over 68 years Helmut Sick conducted an ornithological diary with very detailed, sometimes even artistic descriptions of his observations. His notes between 1923 and 1938 comprise 12 diary books with 80 pages each. The authors secured the material and looked through it. Here a short description of the contents is given. A publication list and more material are available online (see bottom of the text). Helmut Sick died in a traffic accident on 5th March 1991 in Rio de Janeiro