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In the past, the problem of semantic interoperability in information systems was mostly solved by means of centralization, both at a system and at a logical level. This approach has been successful to a certain extent, but offers limited scalability and fl ...
In this talk we present work on sensor-based motion planning in initially unknown dynamic environments. Motion detection and probabilistic motion modeling are combined with a smooth navigation function to perform on-line path planning and replanning in clu ...
Research into the methods and techniques used in simulating crowds is now reaching maturity, but until now there is no book that focuses on this important topic. Prior approaches have been application-specific focusing on different aspects of collective be ...
This work describes the advancements made in micro and nano patterning via stencil lithography. Stencil lithography is a resist-less and direct pattern technique where a controlled amount of material is deposited through apertures on to a substrate in a va ...
Most hardware predictors are table based (e.g. two-level branch predictors) and have exponential size growth in the number of input bits or features (e.g. previous branch outcomes). This growth severely limits the amount of predictive information that such ...
Communication of distant brain areas provides the basis for integration of complex information in order to adapt to changes in the environment, to process this information, and to generate appropriate behavioral responses necessary for successful behavior ...
We propose a new concept, OSCS, seeking to explain the process by which the firm incorporates open source principles into its business model, as an effective diversification strategy to gain and sustain competitive advantage, in the context of a globally i ...
The purpose of this paper is to extend results by Villemoes and Temlyakov about exponential convergence of Matching Pursuit with some structured dictionaries for ``simple'' functions in finite or infinite dimension. Our results are based on an extension of ...
Sparse approximations to Bayesian inference for nonparametric Gaussian Process models scale linearly in the number of training points, allowing for the application of powerful kernel-based models to large datasets. We present a general framework based on t ...
New variants of the QZ algorithm for solving the generalized eigenvalue problem are proposed. An extension of the small-bulge multishift QR algorithm is developed, which chases chains of many small bulges instead of only one bulge in each QZ iteration. Thi ...
Society for Industrial and Applied Mathematics2006
