Recently the problem of dimensionality reduction (or, subspace learning) has received a lot of interests in many fields of information processing, including data mining, informati...
In this paper, we consider the energy-efficient resource allocation that minimizes a general cost function of average user powers in wireless networks. A class of so-called -fair c...
Xin Wang, Di Wang, Hanqi Zhuang, Salvatore D. Morg...
Cross-domain learning methods have shown promising
results by leveraging labeled patterns from auxiliary domains
to learn a robust classifier for target domain, which
has a limi...
Dong Xu, Ivor Wai-Hung Tsang, Lixin Duan, Stephen ...
This paper reports on an NSF-funded effort now underway to integrate three learning technologies that have emerged and matured over the past decade; each has presented compelling ...
We show that the relevant information of a supervised learning problem is contained up to negligible error in a finite number of leading kernel PCA components if the kernel matche...
Mikio L. Braun, Joachim M. Buhmann, Klaus-Robert M...