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SIGGRAPH
1995
ACM
15 years 10 months ago
Stochastic screening dithering with adaptive clustering
We developa clustereddithering methodthatusesstochasticscreening and is able to perform an adaptive variation of the cluster size. This makes it possible to achieve optimal rendit...
Luiz Velho, Jonas Gomes
NIPS
2007
15 years 8 months ago
Convex Learning with Invariances
Incorporating invariances into a learning algorithm is a common problem in machine learning. We provide a convex formulation which can deal with arbitrary loss functions and arbit...
Choon Hui Teo, Amir Globerson, Sam T. Roweis, Alex...
CGO
2008
IEEE
16 years 1 months ago
Cole: compiler optimization level exploration
Modern compilers implement a large number of optimizations which all interact in complex ways, and which all have a different impact on code quality, compilation time, code size,...
Kenneth Hoste, Lieven Eeckhout
NIPS
1998
15 years 7 months ago
Gradient Descent for General Reinforcement Learning
A simple learning rule is derived, the VAPS algorithm, which can be instantiated to generate a wide range of new reinforcementlearning algorithms. These algorithms solve a number ...
Leemon C. Baird III, Andrew W. Moore
TEC
2008
165views more  TEC 2008»
15 years 6 months ago
Population-Based Incremental Learning With Associative Memory for Dynamic Environments
In recent years, interest in studying evolutionary algorithms (EAs) for dynamic optimization problems (DOPs) has grown due to its importance in real-world applications. Several app...
Shengxiang Yang, Xin Yao