The growing adoption of IT-systems for modeling and executing (business) processes or services has thrust the scientific investigation towards techniques and tools which support more complex forms of process analysis. Many of them, such as conformance checking, process alignment, mining and enhancement, rely on complete observation of past (tracked and logged) executions. In many real cases, ho...

We propose a new way of deriving policy gradient updates for reinforcement learning. Our technique, based on Fourier analysis, recasts integrals that arise with expected policy gradients as convolutions and turns them into multiplications. The obtained analytical solutions allow us to capture the low variance benefits of EPG in a broad range of settings. For the critic, we treat trigonometric a...

We characterize the feature superset of Collaborative Virtual Reality Environments (CVREs) out of existing implementations, and derive a novel component framework for transforming standalone VR tools into full-fledged multithreaded collaborative environments. The contributions of our approach rely on cost-effective techniques for loading graphics rendering, user interaction and network communic...

The design of an experiment can greatly affect its potential to produce statistically conclusive results. In this paper, we offer a method for increasing the statistical informativeness of an experiment through the use of adaptive design optimization. The problem to be solved in adaptive design optimization is identifying an experimental design under which one can infer the underlying model and...

Abstract The strongly nonlinear dynamics of taut strings, traveled by a force moving with uniform velocity, is analyzed. A change variable performed, which recasts the equations motion in terms linearized dynamic displacement, measured from quasi-static response. Under hypothesis load velocity far enough celerity string, system appears form linear PDEs whose coefficients are slowly time. Since ...

Through constant exposure to adult input, in dialogue, children’s language gradually develops into rich linguistic constructions that contain multiple cross-modal elements subtly used together for coherent communicative functions. In this chapter, we retrace children’s pathways into multimodal language acquisition in a scaffolding interactional environment. We begin with the first multimodal bu...

We develop mathematical framework and computational tools for calculating frequency responses of linear time-invariant PDEs in which an independent spatial variable belongs to a compact interval. In conventional studies this computation is done numerically using spatial discretization of differential operators in the evolution equation. In this paper, we introduce an alternative method that avo...

Visual data such as videos are often sampled from complex manifold. We propose leveraging the manifold structure to constrain the deep action feature learning, thereby minimizing the intra-class variations in the feature space and alleviating the over-fitting problem. Considering that manifold can be transferred, layer by layer, from the data domain to the deep features, the manifold priori is ...

We propose a minor extension of the Graph Store Protocol and the SPARQL syntax that should be sufficient to enable the application of rules to some kinds of RDF Streams (as defined by the the RDF Stream Processing W3C Community Group) to generate new RDF streams. The IRI identifying an RDF stream is extended with a query string field-value pair defining a sequence of windows of the stream. The ...

We describe two probabilistic models for unsupervised word-sense disambiguation using parallel corpora. The first model, which we call the Sense model, builds on the work of Diab and Resnik (2002) that uses both parallel text and a sense inventory for the target language, and recasts their approach in a probabilistic framework. The second model, which we call the Concept model, is a hierarchica...