We examine the problem of evaluating selection queries over imprecisely represented objects. Such objects are used either because they are much smaller in size than the precise on...
The Conditional Restricted Boltzmann Machine (CRBM) is a recently proposed model for time series that has a rich, distributed hidden state and permits simple, exact inference. We ...
We present an approach to reconstructing chemical reaction networks from time series measurements of the concentrations of the molecules involved. Our solution strategy combines t...
Subsequence similarity matching in time series databases is an important research area for many applications. This paper presents a new approximate approach for automatic online s...
Model compensation is a standard way of improving the robustness of speech recognition systems to noise. A number of popular schemes are based on vector Taylor series (vts) compen...