Matches in SemOpenAlex for { <https://semopenalex.org/work/W2266589065> ?p ?o ?g. }
Showing items 1 to 97 of
97
with 100 items per page.
- W2266589065 abstract "Humans are confronted with massive amounts of visual information that must be collapsed into meaningful chunks, describing which elements of a visual scene belong together, for efficient recognition of faces or objects. This entails the classic model-selection trade-off: choosing the right inventory of chunks that accurately captures the structure of scenes already observed but is not too specific to their details so that it also generalizes well to new scenes. Here we address this problem by asking two questions: what are the optimal learning strategies for the formation of visual chunks, and do humans employ these strategies during unsupervised learning? We implement an ideal learner that uses Bayesian model comparison, a principled statistical solution for the model-selection problem, to extract and store only those chunks that are minimally sufficient to encode the scenes. We then contrast this model with previous pair-wise associative and iterative accounts of learning in a psychophysical experiment. We show that human performance is well above chance when pair-wise statistics in the scenes contain no relevant information. In contrast to previous accounts of human learning, our ideal Bayesian learner can reproduce the result of the experiment, as well as a large set of previous empirical findings. These results suggest that humans learn new complex information from visual scenes by generating economical representations based on previous experience and not by encoding the full correlational structure of the input." @default.
- W2266589065 created "2016-06-24" @default.
- W2266589065 creator A5018664035 @default.
- W2266589065 creator A5023602087 @default.
- W2266589065 creator A5052042429 @default.
- W2266589065 creator A5073665053 @default.
- W2266589065 date "2007-02-25" @default.
- W2266589065 modified "2023-10-18" @default.
- W2266589065 title "Ideal Bayesian learning in human scene perception" @default.
- W2266589065 hasPublicationYear "2007" @default.
- W2266589065 type Work @default.
- W2266589065 sameAs 2266589065 @default.
- W2266589065 citedByCount "0" @default.
- W2266589065 crossrefType "journal-article" @default.
- W2266589065 hasAuthorship W2266589065A5018664035 @default.
- W2266589065 hasAuthorship W2266589065A5023602087 @default.
- W2266589065 hasAuthorship W2266589065A5052042429 @default.
- W2266589065 hasAuthorship W2266589065A5073665053 @default.
- W2266589065 hasConcept C104317684 @default.
- W2266589065 hasConcept C107673813 @default.
- W2266589065 hasConcept C111472728 @default.
- W2266589065 hasConcept C119857082 @default.
- W2266589065 hasConcept C138885662 @default.
- W2266589065 hasConcept C153180895 @default.
- W2266589065 hasConcept C154945302 @default.
- W2266589065 hasConcept C15744967 @default.
- W2266589065 hasConcept C159423971 @default.
- W2266589065 hasConcept C160234255 @default.
- W2266589065 hasConcept C169760540 @default.
- W2266589065 hasConcept C177264268 @default.
- W2266589065 hasConcept C177769412 @default.
- W2266589065 hasConcept C178253425 @default.
- W2266589065 hasConcept C185592680 @default.
- W2266589065 hasConcept C197654239 @default.
- W2266589065 hasConcept C199360897 @default.
- W2266589065 hasConcept C202444582 @default.
- W2266589065 hasConcept C26760741 @default.
- W2266589065 hasConcept C2776502983 @default.
- W2266589065 hasConcept C2776639384 @default.
- W2266589065 hasConcept C33923547 @default.
- W2266589065 hasConcept C41008148 @default.
- W2266589065 hasConcept C55493867 @default.
- W2266589065 hasConcept C66746571 @default.
- W2266589065 hasConcept C81917197 @default.
- W2266589065 hasConceptScore W2266589065C104317684 @default.
- W2266589065 hasConceptScore W2266589065C107673813 @default.
- W2266589065 hasConceptScore W2266589065C111472728 @default.
- W2266589065 hasConceptScore W2266589065C119857082 @default.
- W2266589065 hasConceptScore W2266589065C138885662 @default.
- W2266589065 hasConceptScore W2266589065C153180895 @default.
- W2266589065 hasConceptScore W2266589065C154945302 @default.
- W2266589065 hasConceptScore W2266589065C15744967 @default.
- W2266589065 hasConceptScore W2266589065C159423971 @default.
- W2266589065 hasConceptScore W2266589065C160234255 @default.
- W2266589065 hasConceptScore W2266589065C169760540 @default.
- W2266589065 hasConceptScore W2266589065C177264268 @default.
- W2266589065 hasConceptScore W2266589065C177769412 @default.
- W2266589065 hasConceptScore W2266589065C178253425 @default.
- W2266589065 hasConceptScore W2266589065C185592680 @default.
- W2266589065 hasConceptScore W2266589065C197654239 @default.
- W2266589065 hasConceptScore W2266589065C199360897 @default.
- W2266589065 hasConceptScore W2266589065C202444582 @default.
- W2266589065 hasConceptScore W2266589065C26760741 @default.
- W2266589065 hasConceptScore W2266589065C2776502983 @default.
- W2266589065 hasConceptScore W2266589065C2776639384 @default.
- W2266589065 hasConceptScore W2266589065C33923547 @default.
- W2266589065 hasConceptScore W2266589065C41008148 @default.
- W2266589065 hasConceptScore W2266589065C55493867 @default.
- W2266589065 hasConceptScore W2266589065C66746571 @default.
- W2266589065 hasConceptScore W2266589065C81917197 @default.
- W2266589065 hasLocation W22665890651 @default.
- W2266589065 hasOpenAccess W2266589065 @default.
- W2266589065 hasPrimaryLocation W22665890651 @default.
- W2266589065 hasRelatedWork W1620759536 @default.
- W2266589065 hasRelatedWork W2073493176 @default.
- W2266589065 hasRelatedWork W2140036133 @default.
- W2266589065 hasRelatedWork W2154711678 @default.
- W2266589065 hasRelatedWork W2396901573 @default.
- W2266589065 hasRelatedWork W2522258376 @default.
- W2266589065 hasRelatedWork W2735055431 @default.
- W2266589065 hasRelatedWork W2799029629 @default.
- W2266589065 hasRelatedWork W2942338827 @default.
- W2266589065 hasRelatedWork W2949467366 @default.
- W2266589065 hasRelatedWork W2950341389 @default.
- W2266589065 hasRelatedWork W2951165067 @default.
- W2266589065 hasRelatedWork W2963903710 @default.
- W2266589065 hasRelatedWork W2992279134 @default.
- W2266589065 hasRelatedWork W3009454144 @default.
- W2266589065 hasRelatedWork W3016340552 @default.
- W2266589065 hasRelatedWork W3041393943 @default.
- W2266589065 hasRelatedWork W3109771530 @default.
- W2266589065 hasRelatedWork W3171895902 @default.
- W2266589065 hasRelatedWork W9770290 @default.
- W2266589065 isParatext "false" @default.
- W2266589065 isRetracted "false" @default.
- W2266589065 magId "2266589065" @default.
- W2266589065 workType "article" @default.