Existing Recurrent Neural Networks (RNNs) are limited in their ability to model dynamical systems with nonlinearities and hidden internal states. Here we use our general framework...
Several optimization techniques are hindered by uncertainties about the control flow in a program, which can generally not be determined by static methods at compile time. We pres...
We obtain analytically, the energy optimal speed profile of a generic multi-speed device with a discrete set of speeds, to execute a given task within a given time. Current implem...
Geometric methods are very intuitive and provide a theoretically solid viewpoint to many optimization problems. SVM is a typical optimization task that has attracted a lot of atte...
Michael E. Mavroforakis, Margaritis Sdralis, Sergi...
We show how to efficiently evaluate generic map-filter-product queries, generalizations of select-project-join (SPJ) queries in relational algebra, based on a combination of two...