Kernel methods have been successfully applied to many machine learning problems. Nevertheless, since the performance of kernel methods depends heavily on the type of kernels being...
Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Jinfeng Y...
A new adaptive algorithm, called LLMS, which employs an array image factor, IA , sandwiched in between two Least Mean Square (LMS) sections, is proposed for different applications ...
Jalal Abdulsayed Srar, Kah-Seng Chung, Ali Mansour
Performing distributed consensus in a network has been an important research problem for several years, and is directly applicable to sensor networks, autonomous vehicle formation...
Daniel Thai, Elizabeth Bodine-Baron, Babak Hassibi
This paper presents new and effective algorithms for learning kernels. In particular, as shown by our empirical results, these algorithms consistently outperform the so-called uni...
Bayesian Kullback Ying—Yang dependence reduction system and theory is presented. Via stochastic approximation, implementable algorithms and criteria are given for parameter lear...