Publications

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Yuille, A. L., & Coughlan, J.. (1999). Visual search: Fundamental bounds, order parameters, and phase transitions. Proc Ieee Workshop On Statistical And Computational Theories Of Vision. Cvpr 1999. Fort Collins, Co. June 1999.
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Yuille, A. L., Coughlan, J., & Zhu, S. Chun. (2000). Unified framework for performance analysis of Bayesian inference. In AeroSense 2000 (pp. 333–346). International Society for Optics and Photonics.
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Yuille, A. L., & Coughlan, J.. (1997). Twenty Questions, Focus of Attention, and A*: A theoretical comparison of optimization strategies. In Energy Minimization Methods in Computer Vision and Pattern Recognition (pp. 195–212). Springer Berlin Heidelberg.
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Coughlan, J., & Yuille, A. L.. (2003). A large deviation theory analysis of Bayesian tree search. Ima Volumes In Mathematics And Its Applications, 133, 1–18.
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Yuille, A. L., Coughlan, J., & Konishi, S.. (2001). The KGBR viewpoint-lighting ambiguity and its resolution by generic constraints. Computer Vision, 2001. Iccv 2001. Proceedings. Eighth Ieee International Conference On, 2, 376–382.
Yuille, A. L., Coughlan, J., & Konishi, S.. (2003). The KGBR viewpoint-lighting ambiguity. Journal Of The Optical Society Of America (Josa) A, 20(1).
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Yuille, A. L., & Coughlan, J.. (1999). High-Level and Generic Models for Visual Search: When does high level knowledge help?. In Computer Vision and Pattern Recognition, 1999. IEEE Computer Society Conference on. (Vol. 2). IEEE.
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Coughlan, J., Yuille, A. L., English, C., & Snow, D.. (1998). Efficient optimization of a deformable template using dynamic programming. In 2013 IEEE Conference on Computer Vision and Pattern Recognition (pp. 747–747). IEEE Computer Society.

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