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» Parameterized Learning Complexity
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ICML
2002
IEEE
14 years 10 months ago
Active + Semi-supervised Learning = Robust Multi-View Learning
In a multi-view problem, the features of the domain can be partitioned into disjoint subsets (views) that are sufficient to learn the target concept. Semi-supervised, multi-view a...
Ion Muslea, Steven Minton, Craig A. Knoblock
ATAL
2010
Springer
13 years 11 months ago
Parameterizing the winner determination problem for combinatorial auctions
Combinatorial auctions have been studied by the multiagent systems community for some time, since these auctions are an effective mechanism for resource allocation when agents are...
David Loker, Kate Larson
FTCGV
2006
118views more  FTCGV 2006»
13 years 9 months ago
Mesh Parameterization Methods and Their Applications
We present a survey of recent methods for creating piecewise linear mappings between triangulations in 3D and simpler domains such as planar regions, simplicial complexes, and sph...
Alla Sheffer, Emil Praun, Kenneth Rose
TVCG
2008
169views more  TVCG 2008»
13 years 9 months ago
Adaptive Geometry Image
We present a novel postprocessing utility called adaptive geometry image (AGIM) for global parameterization techniques that can embed a 3D surface onto a rectangular1 domain. This ...
Chih-Yuan Yao, Tong-Yee Lee
NIPS
2000
13 years 11 months ago
Learning Continuous Distributions: Simulations With Field Theoretic Priors
Learning of a smooth but nonparametric probability density can be regularized using methods of Quantum Field Theory. We implement a field theoretic prior numerically, test its eff...
Ilya Nemenman, William Bialek