Abstract. When faced with the task of building accurate classifiers, active learning is often a beneficial tool for minimizing the requisite costs of human annotation. Traditional ...
Traditional architecture design approaches hide hardware uncertainties from the software stack through overdesign, which is often expensive in terms of power consumption. The recen...
Modern models of relation extraction for tasks like ACE are based on supervised learning of relations from small hand-labeled corpora. We investigate an alternative paradigm that ...
Mike Mintz, Steven Bills, Rion Snow, Daniel Jurafs...
Multi-class classification algorithms are very widely used, but we argue that they are not always ideal from a theoretical perspective, because they assume all classes are characte...
We present an extension of the development of an alternating minimization (AM) method1 for the computation of a specimen's complex transmittance function (magnitude and phase...