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» Linear decomposition algorithm for VLSI design applications
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ICML
2005
IEEE
16 years 4 months ago
Analysis and extension of spectral methods for nonlinear dimensionality reduction
Many unsupervised algorithms for nonlinear dimensionality reduction, such as locally linear embedding (LLE) and Laplacian eigenmaps, are derived from the spectral decompositions o...
Fei Sha, Lawrence K. Saul
SAC
2004
ACM
15 years 9 months ago
A cost-oriented approach for infrastructural design
The selection of a cost-minimizing combination of hardware and network components that satisfy organizational requirements is a complex design problem with multiple degrees of fre...
Danilo Ardagna, Chiara Francalanci, Marco Trubian
IPPS
2006
IEEE
15 years 9 months ago
Parallel FPGA-based all-pairs shortest-paths in a directed graph
With rapid advances in VLSI technology, Field Programmable Gate Arrays (FPGAs) are receiving the attention of the Parallel and High Performance Computing community. In this paper,...
Uday Bondhugula, Ananth Devulapalli, Joseph Fernan...
GECCO
2007
Springer
300views Optimization» more  GECCO 2007»
15 years 10 months ago
A NSGA-II, web-enabled, parallel optimization framework for NLP and MINLP
Engineering design increasingly uses computer simulation models coupled with optimization algorithms to find the best design that meets the customer constraints within a time con...
David J. Powell, Joel K. Hollingsworth
SIGIR
2006
ACM
15 years 9 months ago
Large scale semi-supervised linear SVMs
Large scale learning is often realistic only in a semi-supervised setting where a small set of labeled examples is available together with a large collection of unlabeled data. In...
Vikas Sindhwani, S. Sathiya Keerthi