Category learning in a dynamic world

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Labels direct infants’ attention to commonalities during novel category learning

Recent studies have provided evidence that labeling can influence the outcome of infants’ visual categorization. However, what exactly happens during learning remains unclear. Using eye-tracking, we examined infants’ attention to object parts during learning. Our analysis of looking behaviors during learning provide insights going beyond merely observing the learning outcome. Both labeling and non-labeling phrases facilitated category formation in 12-month-olds but not 8-month-olds (Experiment 1). Non-linguistic sounds did not produce this effect (Experiment 2). Detailed analyses of infants’ looking patterns during learning revealed that only infants who heard labels exhibited a rapid focus on the object part successive exemplars had in common. Although other linguistic stimuli may also be beneficial for learning, it is therefore concluded that labels have a unique impact on categorization

A Developmental Approach to Machine Learning?

Visual learning depends on both the algorithms and the training material. This essay considers the natural statistics of infant- and toddler-egocentric vision. These natural training sets for human visual object recognition are very different from the training data fed into machine vision systems. Rather than equal experiences with all kinds of things, toddlers experience extremely skewed distributions with many repeated occurrences of a very few things. And though highly variable when considered as a whole, individual views of things are experienced in a specific order – with slow, smooth visual changes moment-to-moment, and developmentally ordered transitions in scene content. We propose that the skewed, ordered, biased visual experiences of infants and toddlers are the training data that allow human learners to develop a way to recognize everything, both the pervasively present entities and the rarely encountered ones. The joint consideration of real-world statistics for learning by researchers of human and machine learning seems likely to bring advances in both disciplines

The Cat is Out of the Bag: Previous Experience and Online Comparison Jointly Influence Infant Categorization.

We examined the effect of 4-month-old infants previous experience with dogs and/or cats and their on-line comparison on their learning of the adult-defined category of cat in a visual familiarization task. In Experiment 1, 4-month-old infants (N=97) learning in the laboratory was jointly determined by whether or not they had experience with pets at home and their level of on-line comparison during familiarization. Specifically, only infants with pets at home who were also high comparers during familiarization remembered the individual cat exemplars or formed a summary representation of those cats. In Experiments 2 and 3, 4-month-old infants (N = 33) who were low comparers and/or did not have pets at home failed to discriminate among the individual items. These results are consistent with recent theorizing about the processes of how infants categorical representations are formed, and provide new understanding into how infants categorization unfolds over time

How Infants Learn Categories

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