In this paper we investigate multi-task learning in the context of Gaussian Processes (GP). We propose a model that learns a shared covariance function on input-dependent features...
Edwin V. Bonilla, Kian Ming Chai, Christopher K. I...
Inspired by the underlying relationship between classification capability and the mutual information, in this paper, we first establish a quantitative model to describe the inform...
The interpretation of the EM tomography of microtubules is challenging due to the low SNR and low contrast of the volume data. Therefore, image enhancement is crucial for the subs...
In this paper we study the problem of constructing accurate decision tree models from data streams. Data streams are incremental tasks that require incremental, online, and any-ti...
Due to the large difference between seek time and transfer time in current disk technology, it is advantageous to perform large I/O using a single sequential access rather than mu...