Active learning approaches used in practice are generally optimistic about their certainty with respect to data shift between labeled and unlabeled data. They assume that unknown datapoint labels follow the inductive biases of the active learner. As a result, the most useful datapoint labels— ones that refute current inductive biases—are rarely solicited. We propose an adversarial approach to a...

Existing approaches to active learning are generally optimistic about their certainty with respect to data shift between labeled and unlabeled data. They assume that unknown datapoint labels follow the inductive biases of the active learner. As a result, the most useful datapoint labels—ones that refute current inductive biases— are rarely solicited. We propose a shift-pessimistic approach to a...

In the present work, we investigate the tunability of the magnetic response of a new structure. A lattice of periodically arranged close-packed square conducting rings has been studied for this purpose. Here, instead of enhancing the magnetic activity via resonance, like in split-ring resonators, we concentrate on the analysis of the interactions between these rings. The core idea is to design ...

in this paper, a new revenue efficiency data envelopment analysis (re-dea) approach is considered for finding the most revenue efficient unit with price uncertainty in both optimistic and pessimistic perspectives. the optimistic and pessimistic perspectives use efficient frontier and inefficient frontier, respectively. an integrated model is introduced to find decision making units (dmus) that ...

Quantifying the impact of biochemical compounds on collective cell spreading is an essential element of drug design, with various applications including developing treatments for chronic wounds and cancer. Scratch assays are a technically simple and inexpensive method used to study collective cell spreading; however, most previous interpretations of scratch assays are qualitative and do not pro...

This paper analyses research evidence about the creative environments in the UK television production sector. The industry is reviewed across a number of dimensions: the evolving sentiments and structures of collective creativity; the perception of the actual and the ideal creative environment for television production; the growing levels of uncertainty associated with freelance work; and the k...

Causal models can be regarded as fundamental knowledge bases consisting of rules for generating explanations and predictions. As we all know, such inferences are not free from uncertainty. In an experiment about acquiring causal models by induction, we investigate the impact of the validity of such models on the certainty of inferences. The results indicate that preliminary models are revised i...

A natural idea of decision making under uncertainty is to assign a fair price to different alternatives, and then to use these fair prices to select the best alternative. In this paper, we show how to assign a fair price under different types of uncertainty. 1 Decision Making under Uncertainty: Formulation of the Problem Need for decision making. In many practical situations, we have several al...