Scaling up document-image classifiers to handle an unlimited variety of document and image types poses serious challenges to conventional trainable classifier technologies. Highly...
Abstract. We establish results for the problem of tracking a time-dependent manifold arising in realtime optimization by casting this as a parametric generalized equation. We demon...
is an important optimization for programs that use procedural abstraction. Because inlining trades code size for execution speed, the effectiveness of an inlining algorithm is det...
We study the problem of minimizing the expected cost of binary searching for data where the access cost is not fixed and depends on the last accessed element, such as data stored i...
Gonzalo Navarro, Ricardo A. Baeza-Yates, Eduardo F...
We establish a mistake bound for an ensemble method for classification based on maximizing the entropy of voting weights subject to margin constraints. The bound is the same as a ...