| PATURI, R., RAJASEKARAN, S., and REIF, J.H. (1989), The Light Bulb Problem. in "Second Work shop on Computational Learning Theory, " pp. 261--268. |
....version of the same task. 1 Finally, we analyze the data and compare the performance of our algorithms with that of our volunteers. 2 The Experiment (a) b) Figure 1: a) A sample animal. b) A multiple choice question. Our experimental task is motivated by the so called Light Bulb Problem [3]. In this correlation detection task, there is a collection of light bulbs each of which can either be illuminated or not at each time step. Each light bulb has probability p of being on; all pairs are independent but one, which is on together with probability greater than p 2 : The task is to ....
R. Paturi, S. Rajasekaran, J. H. Reif. The Light Bulb Problem, in "Second Workshop on Computational Learning Theory," pages 261-268, Morgan Kaufmann, San Mateo, CA, 1989.
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PATURI, R., RAJASEKARAN, S., and REIF, J.H. (1989), The Light Bulb Problem. in "Second Work shop on Computational Learning Theory, " pp. 261--268.
No context found.
PATURI, R. (1988), The Light Bulb Problem. Technical Report CS88-- 129, University of California, San Diego.
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