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NIPS
2008
13 years 9 months ago
Automatic online tuning for fast Gaussian summation
Many machine learning algorithms require the summation of Gaussian kernel functions, an expensive operation if implemented straightforwardly. Several methods have been proposed to...
Vlad I. Morariu, Balaji Vasan Srinivasan, Vikas C....
SODA
2008
ACM
105views Algorithms» more  SODA 2008»
13 years 9 months ago
Deterministic random walks on regular trees
Jim Propp's rotor router model is a deterministic analogue of a random walk on a graph. Instead of distributing chips randomly, each vertex serves its neighbors in a fixed or...
Joshua N. Cooper, Benjamin Doerr, Tobias Friedrich...
SODA
2008
ACM
104views Algorithms» more  SODA 2008»
13 years 9 months ago
Ranged hash functions and the price of churn
Ranged hash functions generalize hash tables to the setting where hash buckets may come and go over time, a typical case in distributed settings where hash buckets may correspond ...
James Aspnes, Muli Safra, Yitong Yin
SPLC
2008
13 years 9 months ago
Filtered Cartesian Flattening: An Approximation Technique for Optimally Selecting Features while Adhering to Resource Constraint
Software Product-lines (SPLs) use modular software components that can be reconfigured into different variants for different requirements sets. Feature modeling is a common method...
Jules White, B. Doughtery, Douglas C. Schmidt
UAI
2008
13 years 9 months ago
Dyna-Style Planning with Linear Function Approximation and Prioritized Sweeping
We consider the problem of efficiently learning optimal control policies and value functions over large state spaces in an online setting in which estimates must be available afte...
Richard S. Sutton, Csaba Szepesvári, Alborz...
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