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» The Computational Complexity of Linear Optics
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ECCV
2010
Springer
14 years 3 months ago
Fast Covariance Computation and Dimensionality Reduction for Sub-Window Features in Images
This paper presents algorithms for efficiently computing the covariance matrix for features that form sub-windows in a large multidimensional image. For example, several image proc...
IPPS
2008
IEEE
14 years 4 months ago
Modeling and predicting application performance on parallel computers using HPC challenge benchmarks
A method is presented for modeling application performance on parallel computers in terms of the performance of microkernels from the HPC Challenge benchmarks. Specifically, the a...
Wayne Pfeiffer, Nicholas J. Wright
ANSS
1996
IEEE
14 years 2 months ago
Computation of the Asymptotic Bias and Variance for Simulation of Markov Reward Models
The asymptotic bias and variance are important determinants of the quality of a simulation run. In particular, the asymptotic bias can be used to approximate the bias introduced b...
Aad P. A. van Moorsel, Latha A. Kant, William H. S...
TC
2010
13 years 8 months ago
Scalable Node-Level Computation Kernels for Parallel Exact Inference
—In this paper, we investigate data parallelism in exact inference with respect to arbitrary junction trees. Exact inference is a key problem in exploring probabilistic graphical...
Yinglong Xia, Viktor K. Prasanna
AAAI
2006
13 years 11 months ago
Computing Slater Rankings Using Similarities among Candidates
Voting (or rank aggregation) is a general method for aggregating the preferences of multiple agents. One important voting rule is the Slater rule. It selects a ranking of the alte...
Vincent Conitzer