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Learning-Based Approach to Estimation of Morphable Model Parameters

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dc.contributor.author Kumar, Vinay en_US
dc.contributor.author Poggio, Tomaso en_US
dc.date.accessioned 2004-10-20T21:04:37Z
dc.date.available 2004-10-20T21:04:37Z
dc.date.issued 2000-09-01 en_US
dc.identifier.other AIM-1696 en_US
dc.identifier.other CBCL-191 en_US
dc.identifier.uri http://hdl.handle.net/1721.1/7264
dc.description.abstract We describe the key role played by partial evaluation in the Supercomputing Toolkit, a parallel computing system for scientific applications that effectively exploits the vast amount of parallelism exposed by partial evaluation. The Supercomputing Toolkit parallel processor and its associated partial evaluation-based compiler have been used extensively by scientists at MIT, and have made possible recent results in astrophysics showing that the motion of the planets in our solar system is chaotically unstable. en_US
dc.format.extent 1037544 bytes
dc.format.extent 218112 bytes
dc.format.mimetype application/postscript
dc.format.mimetype application/pdf
dc.language.iso en_US
dc.relation.ispartofseries AIM-1696 en_US
dc.relation.ispartofseries CBCL-191 en_US
dc.title Learning-Based Approach to Estimation of Morphable Model Parameters en_US


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