This article proposes a stochastic version of the matching pursuit algorithm for Bayesian variable selection in linear regression. In the Bayesian formulation, the prior distributi...
Exact computation for aggregate queries usually requires large amounts of memory ? constrained in data-streaming ? or communication ? constrained in distributed computation ? and ...
We experimentally evaluate bagging and six other randomization-based approaches to creating an ensemble of decision-tree classifiers. Bagging uses randomization to create multipl...
Robert E. Banfield, Lawrence O. Hall, Kevin W. Bow...
— In this paper, we present an analytical method to evaluate the bit error rate (BER) of the ultra-wideband (UWB) system in the IEEE 802.15.4a standardized channel model. The IEE...
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...