Rejoinder: Classifier Technology and the Illusion of Progress

Rejoinder: Classifier Technology and the Illusion of Progress [math.ST/0606441]Comment: Published at http://dx.doi.org/10.1214/088342306000000079 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Discussion of "Bayesian Models and Methods in Public Policy and Government Settings" by S. E. Fienberg

Fienberg convincingly demonstrates that Bayesian models and methods represent a powerful approach to squeezing illumination from data in public policy settings. However, no school of inference is without its weaknesses, and, in the face of the ambiguities, uncertainties, and poorly posed questions of the real world, perhaps we should not expect to find a formally correct inferential strategy which can be universally applied, whatever the nature of the question: we should not expect to be able to identify a "norm" approach. An analogy is made between George Box's "no models are right, but some are useful," and inferential systems [arXiv:1108.2177].Comment: Published in at http://dx.doi.org/10.1214/11-STS331A the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Guest Editorial: One Size Does Not Fit All, One Critique Does Not Fit All Schools of Education

Many years ago, Dr. Martin Luther King reminded us that skin tone should never be a factor to judge an individual, but rather the content of the individual’s character is the issue to be considered. Just a few years ago the sociologists Lawrence Harrington and Samuel Huntington (2000) completed a study which addresses Max Weber’s premise that culture does matter when looking at the differing levels of societal effectiveness. As we read Dr. Arthur Levine’s Educating School Leaders, we question if Dr. Levine has operated from the understanding that the differences in schools of education are numerous and that each must be evaluated based on the content and outputs of their programs

Bayesian anomaly detection methods for social networks

Learning the network structure of a large graph is computationally demanding, and dynamically monitoring the network over time for any changes in structure threatens to be more challenging still. This paper presents a two-stage method for anomaly detection in dynamic graphs: the first stage uses simple, conjugate Bayesian models for discrete time counting processes to track the pairwise links of all nodes in the graph to assess normality of behavior; the second stage applies standard network inference tools on a greatly reduced subset of potentially anomalous nodes. The utility of the method is demonstrated on simulated and real data sets.Comment: Published in at http://dx.doi.org/10.1214/10-AOAS329 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Intelligent Agents for Disaster Management

ALADDIN [1] is a multi-disciplinary project that is developing novel techniques, architectures, and mechanisms for multi-agent systems in uncertain and dynamic environments. The application focus of the project is disaster management. Research within a number of themes is being pursued and this is considering different aspects of the interaction between autonomous agents and the decentralised system architectures that support those interactions. The aim of the research is to contribute to building more robust multi-agent systems for future applications in disaster management and other similar domains

Navigation and interaction in a real-scale digital mock-up using natural language and user gesture

This paper tries to demonstrate a very new real-scale 3D system and sum up some firsthand and cutting edge results concerning multi-modal navigation and interaction interfaces. This work is part of the CALLISTO-SARI collaborative project. It aims at constructing an immersive room, developing a set of software tools and some navigation/interaction interfaces. Two sets of interfaces will be introduced here: 1) interaction devices, 2) natural language (speech processing) and user gesture. The survey on this system using subjective observation (Simulator Sickness Questionnaire, SSQ) and objective measurements (Center of Gravity, COG) shows that using natural languages and gesture-based interfaces induced less cyber-sickness comparing to device-based interfaces. Therefore, gesture-based is more efficient than device-based interfaces.FUI CALLISTO-SAR