Background: Co-evolution is the process in which two (or more) sets of orthologs exhibit a similar or correlative pattern of evolution. Co-evolution is a powerful way to learn abo...
Classifier learning methods commonly assume that the training data consist of randomly drawn examples from the same distribution as the test examples about which the learned model...
We present a unified framework for reasoning about worst-case regret bounds for learning algorithms. This framework is based on the theory of duality of convex functions. It brin...
— This paper focuses on the design of a robust tube-based Model Predictive Control law for the control of constrained mobile robots. A time-varying trajectory tracking error mode...
Ramon Gonzalez, Mirko Fiacchini, Jose Luis Guzman,...
Abstract— This paper addresses the module assignment problem in pinlimited designs under the stacked-Vdd circuit paradigm. A partition-based algorithm is presented for efficient...