Learning-Based Approach to Estimation of Morphable Model Parameters

dc.creator	Kumar, Vinay
dc.creator	Poggio, Tomaso
dc.date	2004-10-20T21:04:37Z
dc.date	2004-10-20T21:04:37Z
dc.date	2000-09-01
dc.date.accessioned	2013-10-09T02:48:50Z
dc.date.available	2013-10-09T02:48:50Z
dc.date.issued	2013-10-09
dc.identifier	AIM-1696
dc.identifier	CBCL-191
dc.identifier	http://hdl.handle.net/1721.1/7264
dc.identifier.uri	http://koha.mediu.edu.my:8181/xmlui/handle/1721
dc.description	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.
dc.format	1037544 bytes
dc.format	218112 bytes
dc.format	application/postscript
dc.format	application/pdf
dc.language	en_US
dc.relation	AIM-1696
dc.relation	CBCL-191
dc.title	Learning-Based Approach to Estimation of Morphable Model Parameters

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