Linear Discriminant Analysis (LDA) is one of the wellknown methods for supervised dimensionality reduction. Over the years, many LDA-based algorithms have been developed to cope w...
We propose a framework for compressive sensing of images with local geometric features. Specifically, let x ∈ RN be an N-pixel image, where each pixel p has value xp. The image...
Rishi Gupta, Piotr Indyk, Eric Price, Yaron Rachli...
In automated synthesis, we transform a specification into a system that is guaranteed to satisfy the specification against all environments. While modelchecking theory has led to...
Many approximation algorithms have been presented in the last decades for hard search problems. The focus of this paper is on cryptographic applications, where it is desired to de...
Predictable allocations of security resources such as police officers, canine units, or checkpoints are vulnerable to exploitation by attackers. Recent work has applied game-theo...
Christopher Kiekintveld, Manish Jain, Jason Tsai, ...