Titlebook: Statistical Network Analysis: Models, Issues, and New Directions; ICML 2006 Workshop o Edoardo Airoldi,David M. Blei,Alice X. Zheng Confere

哎呦

SEVER

acquisition

Inferring Organizational Titles in Online Communicationof these observed relationships can be problematic given there is a shared context among the individuals that isn’t necessarily communicated. This provides a challenge for analysts that wish to explore and understand email archives for legal or historical research.

compassion

Structural Inference of Hierarchies in Networksxample networks, we demonstrate its advantages for the interpretation of network data, the annotation of graphs with edge, vertex and community properties, and the generation of generic null models for further hypothesis testing.

Comedienne

Ordnance

Approximate Kalman Filters for Embedding Author-Word Co-occurrence Data over Time results on per-year co-occurrences of authors and words in the NIPS corpus and on synthetic data, including videos of dynamic embeddings, seem to indicate that the model results in embeddings of co-occurrence data that are meaningful both temporally and contextually.

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Discovering Functional Communities in Dynamical Networksg and successful community-discovery algorithm for weighted networks. We illustrate it with an application to a large biophysical model of the transition from beta to gamma rhythms in the hippocampus.

ureter

set598

Concomitant

Heider vs Simmel: Emergent Features in Dynamic Structuressocial relations. We propose that Simmelian tie theory could explain the same phenomena without resorting to motivational tautologies that characterize psychological explanations. Further, while both theories predict the same equilibrium state, we argue that they suggest different processes by which