We developa clustereddithering methodthatusesstochasticscreening and is able to perform an adaptive variation of the cluster size. This makes it possible to achieve optimal rendit...
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...
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,...
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 ...
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...