Many learning applications are characterized by high dimensions. Usually not all of these dimensions are relevant and some are redundant. There are two main approaches to reduce d...
We study the complexity of approximating the smallest eigenvalue of −∆ + q with Dirichlet boundary conditions on the d-dimensional unit cube. Here ∆ is the Laplacian, and th...
A popular approach for dimensionality reduction and data analysis is principal component analysis (PCA). A limiting factor with PCA is that it does not inform us on which of the o...
Mahdokht Masaeli, Yan Yan, Ying Cui, Glenn Fung, J...
—We propose a dynamic spectrum access scheme where secondary users recommend “good” channels to each other and access accordingly. We formulate the problem as an average rewa...
Ultra-deep submicron manufacturability impacts physical design (PD) through complex layout rules and large guardbands for process variability; this creates new requirements for ne...