We consider the problem of actively learning the mean values of distributions associated with a finite number of options. The decision maker can select which option to generate t...
Abstract. This chapter describes how we used regression rules to improve upon results previously published in the Earth science literature. In such a scientific application of mac...
Mark Schwabacher, Pat Langley, Christopher Potter,...
Abstract. We propose a convex optimization approach to solving the nonparametric regression estimation problem when the underlying regression function is Lipschitz continuous. This...
Dimitris Bertsimas, David Gamarnik, John N. Tsitsi...
We propose a fully Bayesian approach for generalized kernel models (GKMs), which are extensions of generalized linear models in the feature space induced by a reproducing kernel. ...
Zhihua Zhang, Guang Dai, Donghui Wang, Michael I. ...
Let f be a function on Rd that is monotonic in every variable. There are 2d possible assignments to the directions of monotonicity (two per variable). We provide sufficient condit...