We present a model-based technique for encoding nonrigid object classes in terms of object prototypes. Objects from the same class can be parameterized by identifying shape and appearance invariants of the class to devise lowlevel representations. The approach presented here creates a flexible model for an object class from a set of prototypes. This model is then used to estimate the parameters...

Machine learning methods exploit similarities in users’ activity patterns to provide recommendations applications across a wide range of fields including entertainment, dating, and commerce. However, domains that demand protection personally sensitive data, such as medicine or banking, how can we learn recommendation models without accessing the data inadvertently leaking private information? M...

MODELS 1 Attributes+. . . --, Functional Specifications+. l l + Design Documents Mathematical Models+...+Simulations PHYSICAL REALIZATIONS 0 0 0 BreadboardsBrassboardsProduction Prototypes *----, Production Units Note: @ = Analyses @ = Tests Figure l.The process of validation. ABSTRACT FIODELS: GOALS, AGGREGATE (e.g., MARKOV) MODELS, FAULT TREES, BLOCK DIAGRAMS, FLOW DIAGRAMS, SCHEMATICS, SOURC...

Physical models and scaled prototypes of architecture play an important role in design. They enable architects and designers to investigate the formal, functional, and material attributes of the design. Understanding digital processes of realizing scaled prototypes is a significant problem confronting design practice. This paper reports on three approaches to the translation of Gaussian surface...

As it emerged from philosophical analyses and cognitive research, most concepts exhibit typicality effects, and resist to the efforts of defining them in terms of necessary and sufficient conditions. This holds also in the case of many medical concepts. This is a problem for the design of computer science ontologies, since knowledge representation formalisms commonly adopted in this field (such...