One of the main research concern in neural networks is to find the appropriate network size in order to minimize the trade-off between overfitting and poor approximation. In this ...
We present a new approach for estimation and optimization of the average stand-by power dissipation in large MOS digital circuits. To overcome the complexity of state dependence i...
Supamas Sirichotiyakul, Tim Edwards, Chanhee Oh, J...
Abstract: In this paper we ask the question how much does the neighborhood selection process of a P2P protocol such as Gnutella respect the underlying Internet topology.
Vinay Aggarwal, Stefan Bender, Anja Feldmann, Arne...
Kernel logistic regression models, like their linear counterparts, can be trained using the efficient iteratively reweighted least-squares (IRWLS) algorithm. This approach suggest...
We develop improved risk bounds for function estimation with models such as single hidden layer neural nets, using a penalized least squares criterion to select the size of the mod...