While most popular collaborative filtering methods use low-rank matrix factorization and parametric density assumptions, this article proposes an approach based on distribution-fr...
The paper presents an efficient solution to decision problems where direct partial information on the distribution of the states of nature is available, either by observations of ...
Particle filtering algorithms can be used for the monitoring of dynamic systems with continuous state variables and without any constraints on the form of the probability distribu...
This paper discusses the problem of efficient propagation of uncertain information in dynamic environments and critical situations. When a number of (distributed) agents have only ...
Global depth, tangent depth and simplicial depths for classical and orthogonal regression are compared in examles and properies that are usefull for calculations are derived. Algo...