Journal of Global Optimization
Automated support for classifying software failure reports
Proceedings of the 25th International Conference on Software Engineering
Localization from Connectivity in Sensor Networks
IEEE Transactions on Parallel and Distributed Systems
Shape Classification Using the Inner-Distance
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Knowledge and Data Engineering
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
QoSA'07 Proceedings of the Quality of software architectures 3rd international conference on Software architectures, components, and applications
Locally linear isometric parameterization
EMMCVPR'05 Proceedings of the 5th international conference on Energy Minimization Methods in Computer Vision and Pattern Recognition
Isometric embedding of facial surfaces into S3
Scale-Space'05 Proceedings of the 5th international conference on Scale Space and PDE Methods in Computer Vision
A graph-based feature combination approach to object tracking
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part II
SHREC'10 track: correspondence finding
EG 3DOR'10 Proceedings of the 3rd Eurographics conference on 3D Object Retrieval
SHREC'10 track: non-rigid 3D shape retrieval
EG 3DOR'10 Proceedings of the 3rd Eurographics conference on 3D Object Retrieval
Volume visualization and visual queries for large high-dimensional datasets
VISSYM'04 Proceedings of the Sixth Joint Eurographics - IEEE TCVG conference on Visualization
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This book introduces MDS as a psychological model and as a data analysis technique for the applied researcher. It also discusses, in detail, how to use two MDS programs, Proxscal (a module of SPSS) and Smacof (an R-package). The book is unique in its orientation on the applied researcher, whose primary interest is in using MDS as a tool to build substantive theories. This is done by emphasizing practical issues (such as evaluating model fit), by presenting ways to enforce theoretical expectations on the MDS solution, and by discussing typical mistakes that MDS users tend to make. The primary audience of this book are psychologists, social scientists, and market researchers. No particular background knowledge is required, beyond a basic knowledge of statistics.