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» Parameterized Complexity and Approximation Algorithms
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DAC
2007
ACM
16 years 27 days 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 4 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»
14 years 11 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
15 years 6 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 1 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...