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» Parameterized Complexity and Approximation Algorithms
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DAC
2007
ACM
16 years 7 months ago
An Effective Guidance Strategy for Abstraction-Guided Simulation
tive Guidance Strategy for Abstraction-Guided Simulation Flavio M. De Paula Alan J. Hu Department of Computer Science, University of British Columbia, {depaulfm, ajh}@cs.ubc.ca D...
Flavio M. de Paula, Alan J. Hu
ICPADS
1994
IEEE
15 years 10 months ago
Stochastic Modeling of Scaled Parallel Programs
Testingthe performance scalabilityof parallelprograms can be a time consuming task, involving many performance runs for different computer configurations, processor numbers, and p...
Allen D. Malony, Vassilis Mertsiotakis, Andreas Qu...
IJON
2007
184views more  IJON 2007»
15 years 6 months ago
Convex incremental extreme learning machine
Unlike the conventional neural network theories and implementations, Huang et al. [Universal approximation using incremental constructive feedforward networks with random hidden n...
Guang-Bin Huang, Lei Chen
COMPGEOM
2009
ACM
16 years 1 months ago
Coresets for polytope distance
Following recent work of Clarkson, we translate the coreset framework to the problems of finding the point closest to the origin inside a polytope, finding the shortest distance...
Bernd Gärtner, Martin Jaggi
CVPR
2008
IEEE
16 years 8 months ago
Principled fusion of high-level model and low-level cues for motion segmentation
High-level generative models provide elegant descriptions of videos and are commonly used as the inference framework in many unsupervised motion segmentation schemes. However, app...
Arasanathan Thayananthan, Masahiro Iwasaki, Robert...