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IDEAL
2004
Springer
13 years 10 months ago
Kernel Density Construction Using Orthogonal Forward Regression
Abstract— The paper presents an efficient construction algorithm for obtaining sparse kernel density estimates based on a regression approach that directly optimizes model gener...
Sheng Chen, Xia Hong, Chris J. Harris
JAIR
2011
144views more  JAIR 2011»
12 years 11 months ago
Non-Deterministic Policies in Markovian Decision Processes
Markovian processes have long been used to model stochastic environments. Reinforcement learning has emerged as a framework to solve sequential planning and decision-making proble...
Mahdi Milani Fard, Joelle Pineau
TSMC
2010
12 years 11 months ago
Probability Density Estimation With Tunable Kernels Using Orthogonal Forward Regression
A generalized or tunable-kernel model is proposed for probability density function estimation based on an orthogonal forward regression procedure. Each stage of the density estimat...
Sheng Chen, Xia Hong, Chris J. Harris
IPPS
2009
IEEE
13 years 11 months ago
A cross-input adaptive framework for GPU program optimizations
Abstract—Recent years have seen a trend in using graphic processing units (GPU) as accelerators for general-purpose computing. The inexpensive, single-chip, massively parallel ar...
Yixun Liu, Eddy Z. Zhang, Xipeng Shen
GECCO
2005
Springer
133views Optimization» more  GECCO 2005»
13 years 10 months ago
Parsing and translation of expressions by genetic programming
We have investigated the potential for using genetic programming to evolve compiler parsing and translation routines for processing arithmetic and logical expressions as they are ...
David Jackson