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» Input Modeling Using Quantile Statistical Methods
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HPCA
2008
IEEE
16 years 21 days ago
Roughness of microarchitectural design topologies and its implications for optimization
Recent advances in statistical inference and machine learning close the divide between simulation and classical optimization, thereby enabling more rigorous and robust microarchit...
Benjamin C. Lee, David M. Brooks
SIGCOMM
1996
ACM
15 years 4 months ago
On the Relevance of Long-Range Dependence in Network Traffic
There is much experimental evidence that network traffic processes exhibit ubiquitous properties of self-similarity and long-range dependence, i.e., of correlations over a wide ran...
Matthias Grossglauser, Jean-Chrysostome Bolot
CVPR
2009
IEEE
16 years 7 months ago
Learning General Optical Flow Subspaces for Egomotion Estimation and Detection of Motion Anomalies
This paper deals with estimation of dense optical flow and ego-motion in a generalized imaging system by exploiting probabilistic linear subspace constraints on the flow. We dea...
Richard Roberts (Georgia Institute of Technology),...
ENTCS
2006
183views more  ENTCS 2006»
15 years 10 days ago
Metamodel-Based Model Transformation with Aspect-Oriented Constraints
Model transformation means converting an input model available at the beginning of the transformation process to an output model. A widely used approach to model transformation us...
László Lengyel, Tihamer Levendovszky...
ICML
2004
IEEE
16 years 1 months ago
Parameter space exploration with Gaussian process trees
Computer experiments often require dense sweeps over input parameters to obtain a qualitative understanding of their response. Such sweeps can be prohibitively expensive, and are ...
Robert B. Gramacy, Herbert K. H. Lee, William G. M...