In this paper we present a new framework for collision and self-collision detection for highly deformable objects such as cloth. It permits to efficiently trade off accuracy for s...
This paper introduces a simple and very general theory of compressive sensing. In this theory, the sensing mechanism simply selects sensing vectors independently at random from a ...
We introduce a new jump strategy for look-ahead based satisfiability (Sat) solvers that aims to boost their performance on satisfiable formulae, while maintaining their behavior o...
Determinantal point processes (DPPs), which arise in random matrix theory and quantum physics, are natural models for subset selection problems where diversity is preferred. Among...
—Outlier mining is a major task in data analysis. Outliers are objects that highly deviate from regular objects in their local neighborhood. Density-based outlier ranking methods...