Abstract. We are interested in the relationship between learning efficiency and representation in the case of supervised neural networks for pattern classification trained by conti...
Abstract. Structural hallmarks of language can be explained in terms of adaptation, by language, to pressures arising during its cultural transmission. Here I present a model which...
In this paper we present the Dynamic Grow-Shrink Inference-based Markov network learning algorithm (abbreviated DGSIMN), which improves on GSIMN, the state-ofthe-art algorithm for...
This paper presents a novel approach to reducing the complexity of the transient linear circuit analysis for a hybrid structured clock network. Topology reduction is first used to...
Yi Zou, Yici Cai, Qiang Zhou, Xianlong Hong, Sheld...
Network visualisations use clustering approaches to simplify the presentation of complex graph structures. We present a novel application of clustering algorithms, which controls ...