This paper proposes a compressive sampling scheme based on random temporal sampling using a successive approximation register (SAR) ADC architecture. Variable wordlength data samp...
We introduce a computationally feasible, "constructive" active learning method for binary classification. The learning algorithm is initially formulated for separable cl...
: se the concept of visualizing general abstract data by intermediate projection into the hyperbolic space. Its favorable properties were reported earlier and led to the "hype...
Estimating missing sensor values is an inherent problem in sensor network applications; however, existing data estimation approaches do not apply well to the context of datastream...
Star schema has been a typical model for both online transaction processing in traditional databases and online analytical processing in large data warehouses. In the star schema,...