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» Self-Explanatory Simulations: Scaling Up to Large Models
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ECML
2007
Springer
15 years 3 months ago
Principal Component Analysis for Large Scale Problems with Lots of Missing Values
Abstract. Principal component analysis (PCA) is a well-known classical data analysis technique. There are a number of algorithms for solving the problem, some scaling better than o...
Tapani Raiko, Alexander Ilin, Juha Karhunen
JMLR
2006
156views more  JMLR 2006»
14 years 9 months ago
Large Scale Multiple Kernel Learning
While classical kernel-based learning algorithms are based on a single kernel, in practice it is often desirable to use multiple kernels. Lanckriet et al. (2004) considered conic ...
Sören Sonnenburg, Gunnar Rätsch, Christi...
CGF
2006
111views more  CGF 2006»
14 years 9 months ago
Efficient Large Scale Acquisition of Building Interiors
We describe a system for the rapid acquisition of building interiors. In 40 hours, a two member team with a single acquisition device captured a model of the corridors and 20 indi...
Gleb Bahmutov, Voicu Popescu, Mihai Mudure
HOTOS
2007
IEEE
15 years 1 months ago
Optimizing Power Consumption in Large Scale Storage Systems
Data centers are the backend for a large number of services that we take for granted today. A significant fraction of the total cost of ownership of these large-scale storage syst...
Lakshmi Ganesh, Hakim Weatherspoon, Mahesh Balakri...
SAC
2008
ACM
14 years 9 months ago
Large-scale simulation of V2V environments
Providing vehicles with enhanced ability to communicate and exchange real-time data with neighboring vehicles opens up a variety of complex challenges that can only be met by comb...
Hugo Conceição, Luís Damas, M...