We have studied two efficient sampling methods, Langevin and Hessian adapted Metropolis Hastings (MH), applied to a parameter estimation problem of the mathematical model (Lorent...
Abstract. Machine learning can be utilized to build models that predict the runtime of search algorithms for hard combinatorial problems. Such empirical hardness models have previo...
Frank Hutter, Youssef Hamadi, Holger H. Hoos, Kevi...
It is well known that trivariate reduction — a method to generate two dependent random variables from three independent random variables — can be used to generate Poisson rand...
A model based structural recognition approach is used for 3D detection and localization of vehicles. It is theoretically founded by syntactic pattern recognition using coordinate g...
We study the problem of offering publish/subscribe functionality on top of structured overlay networks using data models and languages from IR. We show how to achieve this by ext...