Abstract--Suppose for a given classification or function approximation (FA) problem data are collected using sensors. From the output of the th sensor, features are extracted, ther...
In this paper, a general method for the numerical solution of maximum-likelihood estimation (MLE) problems is presented; it adopts the deterministic learning (DL) approach to find ...
This paper addresses the problem of interactively modeling large street networks. We introduce a modeling framework that uses tensor fields to guide the generation of a street gra...
Guoning Chen, Gregory Esch, Peter Wonka, Pascal M&...
In this paper, we first propose a new continuous action-set learning automaton and theoretically study its convergence properties and show that it converges to the optimal action....
Modern network processor systems require the ability to adapt their processing capabilities at runtime to changes in network traffic. Traditionally, network processor applications ...