Mixtures of Gaussians are a crucial statistical modeling tool at the heart of many challenging applications in computer vision and machine learning. In this paper, we first descri...
We present a novel detailed placement technique that accounts for systematic through-pitch variations to reduce leakage. Leakage depends nearly exponentially on linewidth (gate le...
Within the geographic domain, an important class of relies on geometric abstractions in the form of lines where, for instance, transportation networks and trajectories of movement...
In the era of deep sub-wavelength lithography for nanometer VLSI designs, manufacturability and yield issues are critical and need to be addressed during the key physical design i...
The main goal of this paper is to develop deeper insights into viable placement-level optimization of routing. Two primary contributions are made. First, an experimental framework...