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COCO
2001
Springer
142views Algorithms» more  COCO 2001»
13 years 9 months ago
On the Complexity of Approximating the VC Dimension
We study the complexity of approximating the VC dimension of a collection of sets, when the sets are encoded succinctly by a small circuit. We show that this problem is • Σp 3-...
Elchanan Mossel, Christopher Umans
IJCNN
2000
IEEE
13 years 9 months ago
VC Dimension Bounds for Product Unit Networks
A product unit is a formal neuron that multiplies its input values instead of summingthem. Furthermore, it has weights acting as exponents instead of being factors. We investigate...
Michael Schmitt
COLT
2003
Springer
13 years 9 months ago
Learning with Rigorous Support Vector Machines
We examine the so-called rigorous support vector machine (RSVM) approach proposed by Vapnik (1998). The formulation of RSVM is derived by explicitly implementing the structural ris...
Jinbo Bi, Vladimir Vapnik
VC
2008
131views more  VC 2008»
13 years 4 months ago
Motion synthesis with decoupled parameterization
In real-time animation systems, motion interpolation techniques are widely used for their controllability and efficiency. The techniques sample the parameter space using example mo...
Dongwook Ha, JungHyun Han
COLT
1993
Springer
13 years 8 months ago
Bounding the Vapnik-Chervonenkis Dimension of Concept Classes Parameterized by Real Numbers
The Vapnik-Chervonenkis (V-C) dimension is an important combinatorial tool in the analysis of learning problems in the PAC framework. For polynomial learnability, we seek upper bou...
Paul W. Goldberg, Mark Jerrum