In recent years, gradient-based LSTM recurrent neural networks (RNNs) solved many previously RNN-unlearnable tasks. Sometimes, however, gradient information is of little use for t...
In this paper, we overcome a major drawback of the level set framework: the lack of point correspondences. We maintain explicit backward correspondences from the evolving interfac...
We propose a new approach to adaptive system identification when the system model is sparse. The approach applies the ℓ1 relaxation, common in compressive sensing, to improve t...
This paper presents a study on Hierarchical Surrogate-Assisted Evolutionary Algorithm (HSAEA) using different global surrogate models for solving computationally expensive optimiza...
Zongzhao Zhou, Yew-Soon Ong, My Hanh Nguyen, Dudy ...
Abstract. The Web has been rapidly “deepened” with the prevalence of databases online. On this “deep Web,” numerous sources are structured, providing schema-rich data– Th...