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ICMAS
1998
15 years 7 months ago
Multi-Machine Scheduling - A Multi-Agent Learning Approach
Multi-machine scheduling, that is, the assigment of jobs to machines such that certain performance demands like cost and time effectiveness are fulfilled, is a ubiquitous and comp...
Wilfried Brauer, Gerhard Weiß
ICML
2006
IEEE
16 years 7 months ago
The support vector decomposition machine
In machine learning problems with tens of thousands of features and only dozens or hundreds of independent training examples, dimensionality reduction is essential for good learni...
Francisco Pereira, Geoffrey J. Gordon
BMCBI
2007
147views more  BMCBI 2007»
15 years 6 months ago
Comparative analysis of long DNA sequences by per element information content using different contexts
Background: Features of a DNA sequence can be found by compressing the sequence under a suitable model; good compression implies low information content. Good DNA compression mode...
Trevor I. Dix, David R. Powell, Lloyd Allison, Jul...
EUROGP
2008
Springer
135views Optimization» more  EUROGP 2008»
15 years 8 months ago
Using Genetic Programming for Turing Machine Induction
Abstract. Turing machines are playing an increasingly significant role in Computer Science domains such as bioinformatics. Instead of directly formulating a solution to a problem, ...
Amashini Naidoo, Nelishia Pillay
ICML
2006
IEEE
16 years 7 months ago
Reinforcement learning for optimized trade execution
We present the first large-scale empirical application of reinforcement learning to the important problem of optimized trade execution in modern financial markets. Our experiments...
Yuriy Nevmyvaka, Yi Feng, Michael S. Kearns