Abstract. We study the decision theory of a maximally risk-averse investor — one whose objective, in the face of stochastic uncertainties, is to minimize the probability of ever ...
Noam Berger, Nevin Kapur, Leonard J. Schulman, Vij...
Use of game-theoretic models to address patrolling applications has gained increasing interest in the very last years. The patrolling agent is considered playing a game against an...
Uncertainty is a very important concern in production scheduling since it can cause infeasibilities and production disturbances. Thus scheduling under uncertainty has received a l...
A general framework for solving image inverse problems is introduced in this paper. The approach is based on Gaussian mixture models, estimated via a computationally efficient MAP...
We introduce an affine extension of the Euler tensor which encompasses all of the inertia properties of interest in a convenient linear format, and we show how it transforms under...