Mean-Shift (MS) is a powerful non-parametric clustering method. Although good accuracy can be achieved, its computational cost is particularly expensive even on moderate data sets...
Traditional approaches for sequential logic optimization include (1) explicit state-based techniques such as state minimization, (2) structural techniques such as retiming, and (3...
This paper presents methods for efficient power minimization at circuit and micro-architectural levels. The potential energy savings are strongly related to the energy profile of ...
Robert W. Brodersen, Mark Horowitz, Dejan Markovic...
Maximum likelihood (ML) estimation is widely used in many computer vision problems involving the estimation of geometric parameters, from conic fitting to bundle adjustment for s...
Naive Geography’s premise “Topology matters, metric refines” calls for metric properties that provide opportunities for finergrained distinctions than the purely qualitative...