Abstract— This paper presents i-AA1 , a constructive, incremental learning algorithm for a special class of weightless, self-organizing networks. In i-AA1 , learning consists of ...
Abstract— We describe a general method to transform a non-Markovian sequential decision problem into a supervised learning problem using a K-bestpaths algorithm. We consider an a...
Hidden Markov models (HMMs) are often used for biological sequence annotation. Each sequence feature is represented by a collection of states with the same label. In annotating a ...
We introduce a simplification algorithm for meshes composed of quadrilateral elements. It is reminiscent of edge-collapse based methods for triangle meshes, but takes a novel appr...
There is growing interest in the area of cross-layer design. This paper addresses the problem of multi-user diversity scheduling together with channel prediction. Recent work demo...