We derive a knowledge gradient policy for an optimal learning problem on a graph, in which we use sequential measurements to refine Bayesian estimates of individual edge values i...
In this paper we propose a novel iterative search procedure for multi-objective optimization problems. The iteration process – though derivative free – utilizes the geometry o...
This paper proposes a new approach to describe the salient contours in cluttered scenes. No need to do the preprocessing, such as edge detection, we directly use a set of random s...
We present an efficient optimization scheme for gate sizing in the presence of process variations. Our method is a worst-case design scheme, but it reduces the pessimism involved i...
Jaskirat Singh, Zhi-Quan Luo, Sachin S. Sapatnekar
We present a theory of a modeler's problem decomposition skills in the context of optimal reasonzng -- the use of qualitative modeling to strategically guide numerical explor...