A family of models for category learning is developed, all members being based on a common memory array but differing in memory access and decision processes. Within this framework, fully controlled comparisons of exemplar-similarity, feature-frequency, and prototype models reveal isomorphism between models of different types under some conditions but empirically testable differences under othe...

The exemplar-based image inpainting algorithm consists of two procedures: patch selection and patch estimation. In this paper, we focus on the latter. Conventional exemplar-based approaches cannot fully exploit the information existing in the image, which makes the patch estimation unstable and produces false colors and artifacts. In this paper, we propose a robust patch estimation algorithm fo...

Children’s spatial language abilities relate to their spatial skills. We propose that this relation arises from attention to spatial dimensions influencing both spatial word and spatial skill acquisition. This study tests whether attending to spatial dimensions in a word learning task predicts spatial vocabulary. Three to 5-year-olds completed a novel word assessment testing categorization of a...

Decision-boundary theories of categorization are often difficult to distinguish from exemplar-based theories of categorization. The authors developed a version of the decision-boundary theory, called the single-cutoff model, that can be distinguished from the exemplar theory. The authors present 2 experiments that test this decision-boundary model. The results of both experiments point strongly...

This work studies the use of observation uncertainty measures for improving the speech recognition performance of an exemplar-based source separation based front end. To generate the observation uncertainty estimates for the enhanced features, we propose the use of heuristic methods based on the sparse representation of the noisy signal in the exemplar-based source separation algorithm. The eff...

Kuhl’s native language magnet (NLM) theory of phonetic learning is examined in the light of an exemplar-based model. According to the NLM theory the perceptual space is partitioned into phonetic categories as a consequence of the magnet-like properties of the category’s best exemplar  the category’s prototype. The NLM theory predicts that the perceptual space is warped in the neighborhood of t...