In this paper, we study the interconnect layout optimization problem under a higher-order RLC model to optimize not just delay, but also waveform for RLC circuits with non-monoton...
Abstract. Approaches to data mining proposed so far are mainly symbolic decision trees and numerical feedforward neural networks methods. While decision trees give, in many cases, ...
Abstract. Approximate Policy Iteration (API) is a reinforcement learning paradigm that is able to solve high-dimensional, continuous control problems. We propose to exploit API for...
Input selection is an important consideration in all large-scale modelling problems. We propose that using an established noise variance estimator known as the Delta test as the ta...
Quadratic optimization lies at the very heart of many structural pattern recognition and computer vision problems, such as graph matching, object recognition, image segmentation, ...