Graph databases underlie several modern applications such as social networks and the Semantic Web. In those scenarios, integrating and exchanging data is very common, which leads to proliferation of incomplete graph data. However, the well developed models of incompleteness of data do not apply to graph data. This is mainly due to the fact that standard graph query languages concentrate on grap...

Model selection in complete data is a common task for the applied researcher. However, in many scenarios data are incomplete which further complicates the task of model selection. In this talk, we will specify the problem of model selection in incomplete data and discuss several possible solutions using multiple imputation. First, we will define a new general measure for the correct model selec...

Clinical studies often collect longitudinal and time-to-event data for each subject. Joint modeling is a powerful methodology evaluating the association between these data. The existing models, however, have not sufficiently addressed problem of missing data, which are commonly encountered in studies. In this paper, we introduce novel joint model with shared random effects incomplete Our propos...

We explore the capabilities of Auto-Encoders to fuse the information available from cameras and depth sensors, and to reconstruct missing data, for scene understanding tasks. In particular we consider three input modalities: RGB images; depth images; and semantic label information. We seek to generate complete scene segmentations and depth maps, given images and partial and/or noisy depth and s...

Although the survival benefit of complete revascularization after bypass surgery is well documented, the importance of opening all stenotic or occluded vessels during percutaneous coronary intervention (PCI) is less certain. On the contrary, much data support targeting only the culprit vessel during PCI. A strategy of “ischemic-driven revascularization” is often the standard of care. Through a ...

A “partial” generalization of Fine’s definition [Fin] of normal forms in normal minimal modal logic is given. This means quick access to complete axiomatizations and decidability proofs for partial modal logic [Thi]. Introduction. From the viewpoint of formal linguistics, cognitive science and artificial intelligence, there appears to be a natural interest in the combinations of partiality and ...

Information integration is the task of aggregating data from multiple heterogeneous data sources. The understandings of semantics and context knowledge of data sources are often the keys to challenging problems in information integration such as schema alignments and inconsistency resolution. Context logic provides a unified framework for the modeling of data sources; nevertheless, the acquisit...

Mining frequent patterns is essential in many data mining methods. Frequent patterns lead to the discovery of association rules, strong rules, sequential episodes, and multi-dimensional patterns. Patterns should be discovered in a time and space efficient manner. Vertical mining algorithms key advantage is that they can outperform their horizontal counterparts in terms of both time and space ef...

We give explicit analytical formulas for finding a signal with the known compact support from its spectrum known on a finite frequency band.