Likelihood based inference for multi-state latent factor intensity models is hindered by the fact that exact closed-form expressions for the implied data density are not available. This is a common and well-known problem for most parameter driven dynamic econometric models. This paper reviews, adapts and compares three different approaches for solving this problem. For evaluating the likelihood...

Recent years have seen the development of efficient and provably correct spectral algorithms for learning models of partially observable environments arising in many applications. But despite the high hopes raised by this new class of algorithms, their practical impact is still below expectations. One reason for this is the difficulty in adapting spectral methods to exploit structural constrain...

We investigate the composition of finitestate automata in a multiprocessor environment, presenting a parallel variant of a widely-used composition algorithm. We provide an approximate upper bound for composition speedup of the parallel variant with respect to serial execution, and empirically evaluate the performance of our implementation with respect to this bound.

Collaborative ontology engineering enables the creation of large complex ontologies. However, few projects successfully perform such multi-user ontology modeling. This paper gives an overview of ten different ontology engineering projects’ infrastructure, architecture and workflows. It especially focuses on issues regarding collaborative ontology modeling. The survey leads on to a discussion of...

In evolutionary biology, a character is a function χ from a set X of present-day species into a finite set of states. Suppose the species in X have evolved according to a bifurcating tree T . Biologists would like to use characters to infer this tree. Assume that χ is the result of an evolutionary process on T that has not involved reverse or parallel transitions, such characters are called hom...

The road ahead will be long and the climb will be steep, but I will never terminate pursuit. Preface Traffic and transport research is truly attractive to me. To explore the problem that relates closely to our life also motivates me. This is the reason why I dive into the field of traffic science. After my bachelor graduation in engineering mechanics in Shanghai China, I came to the Netherlands...

During transition, maintaining employment and providing a social safety net to the unemployed are important to social stability, which in turn is crucial for the productivity of the whole economy. Because independent institutions for social safety are lacking and firms with strong profit incentives have little incentives to promote social stability due to its public good nature, state-owned ent...

Minimum Message Length (MML) is an invariant Bayesian point estimation technique which is also consistent and eecient. We provide a brief overview of MML inductive inference (Wallace and Boulton (1968), Wallace and Freeman (1987)), and how it has both an information-theoretic and a Bayesian interpretation. We then outline how MML is used for statistical parameter estimation, and how the MML mix...

The generalization ability of an extremely dilute feedback neural network with multistate neurons is studied by means of a deterministic noiseless parallel dynamics. The overlap with any one of a macroscopic number of binary, full activity, concepts is determined when the network is trained with examples of variable activity according to a Hebbian learning algorithm that favours stable symmetri...

State estimation in the energy management center of active distribution networks has attracted many attentions. Considering an increase in complexity and real-time management of active distribution networks and knowing the network information at each time instant are necessary. This article presents a two-step multi-area state estimation method in balanced active distribution networks. The prop...