Ensemble learning is a variational Bayesian method in which an intractable distribution is approximated by a lower-bound. Ensemble learning results in models with better generaliz...
— Gene expression based cancer classification using classifier ensembles is the main focus of this work. A new ensemble method is proposed that combines predictions of a small ...
—As mobile nodes roam in a wireless network, they continuously associate with different access points and perform handoff operations. However, these handoffs can potentially incu...
Minkyong Kim, Zhen Liu, Srinivasan Parthasarathy 0...
Graph structure can model the relationships among a set of objects. Mining quasi-clique patterns from large dense graph data makes sense with respect to both statistic and applica...
Abstract—We show that signal strength variability can be reduced by employing multiple low-cost antennas at fixed locations. We further explore the impact of this reduction on w...
Konstantinos Kleisouris, Yingying Chen, Jie Yang, ...