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Probabilistic Principles In Unsupervised Learning Of Visual Structure: Human Data And A Model, Shimon Edelman, Benjamin P. Hiles, Hwajin Yang, Nathan Intrator
Probabilistic Principles In Unsupervised Learning Of Visual Structure: Human Data And A Model, Shimon Edelman, Benjamin P. Hiles, Hwajin Yang, Nathan Intrator
Research Collection School of Social Sciences
To find out how the representations of structured visual objects depend on the co-occurrence statistics of their constituents, we exposed subjects to a set of composite images with tight control exerted over (1) the conditional probabilities of the constituent fragments, and (2) the value of Barlow's criterion of "suspicious coincidence" (the ratio of joint probability to the product of marginals). We then compared the part verification response times for various probe/target combinations before and after the exposure. For composite probes, the speedup was much larger for targets that contained pairs of fragments perfectly predictive of each other, compared to those …