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Spreadsheets are widely recognized as popular programming systems with a huge number of spreadsheets being created every day. Also, spreadsheets are often used in the decision processes of profit-oriented companies. While this illustrates their practical importance, studies have shown that up to 90% of real-world spreadsheets contain errors.
In numerous neuroscience studies, multichannel EEG data are often recorded over multiple trial periods under the same experimental condition. To date, little effort is aimed to learn spatial patterns from EEG data to account for trial-to-trial variability. In this paper, a hierarchical Bayesian framework is introduced to model inter-trial source variability while extracting common spatial patterns...
We present an approach to the inference of automata models of Web-based business applications using only execution traces recording the externally observable behavior of such applications. The proposed approach yields behavioral models representing both the control flow of an application and the data variations corresponding to different types of users. We also describe how the obtained models allow...
We describe the implementation and performance of a compression-based model inference engine, MDLcompress. The MDL-based compression produces a two part code of the training data, with the model portion of the code being used to compress and classify test data. We present pseudo-code of the algorithms for model generation and explore the conflicting requirements between minimizing grammar size and...
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