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ICML
2010
IEEE
13 years 11 months ago
Feature Selection Using Regularization in Approximate Linear Programs for Markov Decision Processes
Approximate dynamic programming has been used successfully in a large variety of domains, but it relies on a small set of provided approximation features to calculate solutions re...
Marek Petrik, Gavin Taylor, Ronald Parr, Shlomo Zi...
ICPP
1999
IEEE
14 years 2 months ago
Compiler Optimizations for I/O-Intensive Computations
This paper describes transformation techniques for out-of-core programs (i.e., those that deal with very large quantities of data) based on exploiting locality using a combination...
Mahmut T. Kandemir, Alok N. Choudhary, J. Ramanuja...
GECCO
2008
Springer
174views Optimization» more  GECCO 2008»
13 years 11 months ago
Mask functions for the symbolic modeling of epistasis using genetic programming
The study of common, complex multifactorial diseases in genetic epidemiology is complicated by nonlinearity in the genotype-to-phenotype mapping relationship that is due, in part,...
Ryan J. Urbanowicz, Nate Barney, Bill C. White, Ja...
CHARME
2003
Springer
196views Hardware» more  CHARME 2003»
14 years 3 months ago
Analyzing the Intel Itanium Memory Ordering Rules Using Logic Programming and SAT
We present a non-operational approach to specifying and analyzing shared memory consistency models. The method uses higher order logic to capture a complete set of ordering constra...
Yue Yang, Ganesh Gopalakrishnan, Gary Lindstrom, K...
ECML
2004
Springer
14 years 1 months ago
Efficient Hyperkernel Learning Using Second-Order Cone Programming
The kernel function plays a central role in kernel methods. Most existing methods can only adapt the kernel parameters or the kernel matrix based on empirical data. Recently, Ong e...
Ivor W. Tsang, James T. Kwok