Decision makers that employ state abstraction (or state aggregation) usually find solutions faster by treating groups of states as indistinguishable by ignoring irrelevant state information. Identifying irrelevant information is essential for the field of knowledge transfer where learning takes place in a general setting for multiple domains. We provide a general treatment and algorithm for tra...

A popular machine learning strategy is the transfer of a representation (i.e. a feature extraction function) learned on a source task to a target task. Examples include the re-use of neural network weights or word embeddings. Our work proposes novel and general sufficient conditions for the success of this approach. If the representation learned from the source task is fixed, we identify condit...

Application flows naturally from good science, and behavioral toxicology is no exception. Phenomena discovered and procedures developed in behavioral laboratories are being applied on a wide scale in commercial, industrial, and governmental settings. In behavioral toxicology, this transfer of technology has occurred in an ad hoc manner, albeit with a degree of sophistication. The development of...

Machine learning approaches to indoor WiFi localization involve an offline phase and an online phase. In the offline phase, data are collected from an environment to build a localization model, which will be applied to new data collected in the online phase for location estimation. However, collecting the labeled data across an entire building would be too time consuming. In this paper, we pres...

This review provides a brief description of gene transfer studies using salivary glands as the target tissue. The aggregate results demonstrate the potential clinical value of this methodological approach for managing several conditions lacking fully satisfactory conventional treatments. Routine clinical applications are still seven to ten years away, primarily because of the need for improved ...

This paper discusses some of the necessary prerequisites for transferring speciication analysis and veriication techniques from VDM to Z. It starts by comparing Z and VDM in terms of the mathematical and speciication notations they use. It then explains the VDM approach to reasoning about speciications, as supported by the mural tool-set, and compares VDM's Logic of Partial Functions with Class...