The way people respond to the chance that an unlikely event will occur depends on how the event is described. We propose that people attach more weight to unlikely events when they can easily generate or imagine examples in which the event has occurred or will occur than when they cannot. We tested this idea in two experiments with mock jurors using written murder scenarios. The results suggest...

The idea that natural phenomena can be explained by means of exemplars or explanations of previous phenomena has often been proposed in the literature but never formally worked out. To the best of my knowledge, no exact mechanism exists that models new phenomena on previous ones, or that describes how problem solutions can be reused to explain new cases in science. In this paper, I attempt to d...

This paper describes ongoing work on distributional models for word meaning in context. We abandon the usual one-vectorper-word paradigm in favor of an exemplar model that activates only relevant occurrences. On a paraphrasing task, we find that a simple exemplar model outperforms more complex state-of-the-art models.

this paper reports a survey and case study research outcomes on the application of data envelopment analysis (dea) to the ranking method of european foundation for quality management (efqm) business excellence model in iran’s automotive industry and improving benchmarking process after assessment. following the global trend, the iranian industry leaders have introduced the efqm practice to thei...

In this paper, we present a survey of the approximability and fixed-parameter tractability results for some Exemplar Genomic Distance problems. We mainly focus on three problems: the exemplar breakpoint distance problem and its complement (i.e., the exemplar non-breaking similarity or the exemplar adjacency number problem), and the maximal strip recovery (MSR) problem. The following results hol...

Recognizing and reasoning about the objects found in an image is one of the key problems in computer vision. This thesis is based on the idea that in order to understand a novel object, it is often not enough to recognize the object category it belongs to (i.e., answering “What is this?”). We argue that a more meaningful interpretation can be obtained by linking the input object with a similar ...

Previous functional imaging studies have shown that facilitated processing of a visual object on repeated, relative to initial, presentation (i.e., repetition priming) is associated with reductions in neural activity in multiple regions, including fusiform/lateral occipital cortex. Moreover, activity reductions have been found, at diminished levels, when a different exemplar of an object is pre...

Previous studies have suggested that individuals use both implicit and explicit, as well as rule and exemplar-based knowledge, to make grammaticality judgments in artificial grammar learning (AGL) tasks. Experiment 1 explored the importance of explicit mechanisms in the learning of exemplar and rule-based information by using a dual-task during AGL training. We utilized a balanced chunk strengt...

Exemplar theories of categorization depend on similarity for explaining subjects' ability to generalize to new stimuli. A major criticism of exemplar theories concerns their lack of abstraction mechanisms and thus, seemingly, of generalization ability. Here, we use insights from machine learning to demonstrate that exemplar models can actually generalize very well. Kernel methods in machine lea...

Realistic rendering of computer modeled three dimensional surfaces typically involves estimation of the reflectance properties of the material to be used for rendering the surface, or use of photographs of the material for texturing instead. Bidirectional texture functions (BTFs) can be used for this purpose, however, full coverage of all viewing and lighting directions desired must be acquired...