We propose a unified manifold learning framework for semi-supervised and unsupervised dimension reduction by employing a simple but effective linear regression function to map the ...
Feiping Nie, Dong Xu, Ivor Wai-Hung Tsang, Changsh...
Compared to Singular Value Decomposition (SVD), Generalized Low Rank Approximations of Matrices (GLRAM) can consume less computation time, obtain higher compression ratio, and yiel...
The cognitive radio (CR) paradigm calls for open spectrum access according to a predetermined etiquette. Under this paradigm, CR nodes access the spectrum opportunistically by cont...
—Approximating ideal program outputs is a common technique for solving computationally difficult problems, for adhering to processing or timing constraints, and for performance ...
Jason Ansel, Yee Lok Wong, Cy P. Chan, Marek Olsze...
Abstract—Widely distributed multiple radar architectures offer parameter estimation improvement for target localization. For a large number of radars, the achievable localization...
Hana Godrich, Athina P. Petropulu, H. Vincent Poor