We propose a language model based on a precise, linguistically motivated grammar (a hand-crafted Head-driven Phrase Structure Grammar) and a statistical model estimating the proba...
We consider the problem of numerical stability and model density growth when training a sparse linear model from massive data. We focus on scalable algorithms that optimize certain...
This paper presents a guaranteed method for the parameter estimation of nonlinear models in a bounded-error context. This method is based on functions which consists of the differ...
J. M. Bravo, T. Alamo, M. J. Redondo, Eduardo F. C...
This paper addresses several issues of using the mathematical programming representations of discrete-event dynamic systems in perturbation analysis. In particular, linear program...
While researchers have invested substantial effort to build architectural power models, validating such models has proven difficult at best. In this paper, we examine the accurac...
Madhu Saravana Sibi Govindan, Stephen W. Keckler, ...