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ICML
2007
IEEE
14 years 11 months ago
Adaptive mesh compression in 3D computer graphics using multiscale manifold learning
This paper investigates compression of 3D objects in computer graphics using manifold learning. Spectral compression uses the eigenvectors of the graph Laplacian of an object'...
Sridhar Mahadevan
WMTE
2002
IEEE
14 years 3 months ago
Applying Wireless Technologies to Build a Highly Interactive Learning Environment
This study tries to apply wireless technologies to build a highly interactive environment. For this purpose, this study first identifies four types of interaction between the memb...
Tzu-Chien Liu, Hsue-Yie Wang, Jen-Kai Liang, Tak-W...
UAI
2003
13 years 11 months ago
Large-Sample Learning of Bayesian Networks is NP-Hard
In this paper, we provide new complexity results for algorithms that learn discrete-variable Bayesian networks from data. Our results apply whenever the learning algorithm uses a ...
David Maxwell Chickering, Christopher Meek, David ...
ICPR
2010
IEEE
13 years 8 months ago
Multiple Kernel Learning with High Order Kernels
Previous Multiple Kernel Learning approaches (MKL) employ different kernels by their linear combination. Though some improvements have been achieved over methods using single kerne...
Shuhui Wang, Shuqiang Jiang, Qingming Huang, Qi Ti...
ICCV
1998
IEEE
15 years 1 days ago
Wormholes in Shape Space: Tracking Through Discontinuous Changes in Shape
Existing object tracking algorithms generally use some form of local optimisation, assuming that an object's position and shape change smoothly over time. In some situations ...
Tony Heap, David Hogg