Abstract. We advocate to analyze the average complexity of learning problems. An appropriate framework for this purpose is introduced. Based on it we consider the problem of learni...
We consider the problem of selecting an optimal set of sensors, as determined, for example, by the predictive accuracy of the resulting sensor network. Given an underlying metric ...
Roman Garnett, Michael A. Osborne, Stephen J. Robe...
One of the key problems in forming a smooth model from input-output data is the determination of which input variables are relevant in predicting a given output. In this paper we ...
Alban P. M. Tsui, Antonia J. Jones, A. Guedes de O...
In this paper, we propose a new technique, referred to as virtual probe (VP), to efficiently measure, characterize and monitor both inter-die and spatially-correlated intra-die va...
Real-world networks often need to be designed under uncertainty, with only partial information and predictions of demand available at the outset of the design process. The field ...