We consider probabilistic constrained linear programs with general distributions for the uncertain parameters. These problems generally involve non-convex feasible sets. We develo...
We present a new algorithm to jointly track multiple objects in multi-view images. While this has been typically addressed separately in the past, we tackle the problem as a single...
Laura Leal-Taixe, Gerard Pons-Moll, Bodo Rosenhahn
The decision tree is one of the most fundamental ing abstractions. A commonly used type of decision tree is the alphabetic binary tree, which uses (without loss of generality) &quo...
The Constraint Problems usually addressed fall into one of two models: the Constraint Satisfaction Problem (CSP) and the Constraint Optimization Problem (COP). However, in many rea...
We present a practical algorithm that provably achieves the global optimum for a class of bilinear programs commonly arising in computer vision applications. Our approach relies o...