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Aggressive scaling of CMOS technology has enabled faster and smaller designs but has posed new challenges. In the deep-submicron era, leakage power has become a major contributor to the overall power dissipation of an IC. In this paper, we present a weighted partial Max-SAT (WPMax-SAT) based approach to find the minimum leakage vector (MLV) of a combinational design. In its exact form, this technique...
This paper presents an algorithm for online adaptation of the kernel width parameter in information theoretic cost functions used for adaptive system training. Training algorithms which optimize information theoretic quantities like entropy involve choosing a kernel size for their sample estimators. The kernel size essentially dictates the nature of the performance surface of the cost function over...
This paper presents a closed form recursive solution for training adaptive filters using the Maximum Correntropy Criterion (MCC). Correntropy has been recently proposed as a robust similarity measure between two random variables or signals, when the pdfs involved are heavy tailed and non-Gaussian. Maximizing the cross-correntropy between the output of an adaptive filter and the desired response leads...
Correntropy has been recently defined as a localised similarity measure between two random variables, exploiting higher order moments of the data. This paper presents the use of correntropy as a cost function for minimizing the error between the desired signal and the output of an adaptive filter, in order to train the filter weights.We have shown that this cost function has the computational simplicity...
We introduce the coupled placement problem for modern data centers spanning placement of application computation and data among available server and storage resources. While the two have traditionally been addressed independently in data centers, two modern trends make it beneficial to consider them together in a coupled manner: (a) rise in virtualization technologies, which enable applications packaged...
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