Christian Schäfer

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A Monte Carlo algorithm is said to be adaptive if it automatically calibrates its current proposal distribution using past simulations. The choice of the parametric family that defines the set of proposal distributions is critical for good performance. In this paper, we present such a parametric family for adaptive sampling on high-dimensional binary(More)
We discuss a unified approach to stochastic optimization of pseudo-Boolean objective functions based on particle methods, including the cross-entropy method and simulated annealing as special cases. We point out the need for auxiliary sampling distributions, meaning parametric families on binary spaces, which are able to reproduce complex dependency(More)
The design of suitable packet-filters protecting subnets against network based attacks is usually difficult and error-prone. Therefore, tool-assistance shall facilitate the design task and shall contribute to the correctness of the filters, i.e., the filters should be consistent with the other security mechanisms of the computer network, in particular with(More)
This document is the aggregation of several discussions of Lopes et al. (2010) we submitted to conjunction with Hedibert Lopes' talk at this meeting. The main point in those discussions is the potential for degeneracy in the particle learning methodology, related with the exponential forgetting of the past simulations. We illustrate the resulting(More)
Tool support for the development of Domain-specific Languages (DSLs) is continuously increasing. This reduces implementation effort for DSLs and enables the development of rather complex languages within reasonable amounts of time. However, the lack of commonly agreed and applied language engineering processes, many times turns DSL development into a set of(More)
Graphical, well focused and intuitive domain specific languages (DSLs) are more and more used to design parts of embedded systems. These languages are highly specialized and often tailored to one domain; one single language therefore cannot describe all relevant aspects of systems and system components. This raises the need for heterogeneous modeling(More)