It has been proposed that human category learning consists of an early abstraction-based stage followed by a later exemplar-memorization stage. To investigate whether similar processing stages extend to category learning in a nonverbal species, we applied a prototype-exception paradigm to investigating pigeon category learning. Five birds and 8 humans learned six-dimensional perceptual categori...

Exemplar-Based Random-Walk Model 2 Abstract A fundamental issue in cognitive psychology and cognitive science concerns the manner in which people represent categories in memory and make decisions about category membership. In this chapter we provide a review of a process-oriented mathematical model of categorization known as the exemplar-based random-walk (EBRW) model (Nosofsky & Palmeri, 1997a...

This paper addresses the problem of capturing the dynamics for exemplar-based recognition systems. Traditional HMM provides a probabilistic tool to capture system dynamics and in exemplar paradigm, HMM states are typically coupled with the exemplars. Alternatively, we propose a non-parametric HMM approach that uses a discrete HMM with arbitrary states (decoupled from exemplars) to capture the d...

It is generally assumed that when making categorization judgments the cognitive system learns to focus on stimuli features that are relevant for making an accurate judgment. This is a key feature of hybrid categorization systems, which selectively weight the use of exemplar- and rule-based processes. In contrast, Hahn et al. (2010) have shown that people cannot help but pay attention to exempla...

In this paper, we compare two different frameworks for exemplarbased speech recognition and propose a combined system that approximates the input speech as a linear combination of exemplars of variable length. This approach allows us not only to use multiple length long exemplars, each representing a certain speech unit, but also to jointly approximate input speech segments using several exempl...

Erickson and Kruschke (1998, 2002) demonstrated that in rule-plus-exception categorization, people generalize category knowledge by extrapolating in a rule-like fashion, even when they are presented with a novel stimulus that is most similar to a known exception. Although exemplar models have been found to be deficient in explaining rule-based extrapolation, Rodrigues and Murre (2007) offered a...

Recent ideas about category learning have favored exemplar processes over prototype processes. However, research has focused on small, poorly differentiated categories and on task-final performances—both may highlight exemplar strategies. Thus, we evaluated participants' categorization strategies and standard categorization models at successive stages in the learning of smaller, less differenti...

Estimating the precise pose of a 3D model in an image is challenging; explicitly identifying correspondences is difficult, particularly at smaller scales and in the presence of occlusion. Exemplar classifiers have demonstrated the potential of detection-based approaches to problems where precision is required. In particular, correlation filters explicitly suppress classifier response caused by ...

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...