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EMNLP
2007
15 years 8 months ago
What Can Syntax-Based MT Learn from Phrase-Based MT?
We compare and contrast the strengths and weaknesses of a syntax-based machine translation model with a phrase-based machine translation model on several levels. We briefly descr...
Steve DeNeefe, Kevin Knight, Wei Wang 0006, Daniel...
DNA
2003
Springer
101views Bioinformatics» more  DNA 2003»
16 years 1 hour ago
A Lab-on-a-Chip Module for Bead Separation in DNA-Based Concept Learning
Affinity separation with magnetic beads is an important and widely used technique for DNA computing. We have designed and implemented an experimental lab-on-a-chip module for affin...
Hee-Woong Lim, Hae-Man Jang, Sung-Mo Ha, Young-Gyu...
ESANN
2008
15 years 8 months ago
Learning to play Tetris applying reinforcement learning methods
In this paper the application of reinforcement learning to Tetris is investigated, particulary the idea of temporal difference learning is applied to estimate the state value funct...
Alexander Groß, Jan Friedland, Friedhelm Sch...
ICML
2008
IEEE
16 years 7 months ago
Empirical Bernstein stopping
Sampling is a popular way of scaling up machine learning algorithms to large datasets. The question often is how many samples are needed. Adaptive stopping algorithms monitor the ...
Csaba Szepesvári, Jean-Yves Audibert, Volod...
ICML
1998
IEEE
16 years 7 months ago
The Case against Accuracy Estimation for Comparing Induction Algorithms
We analyze critically the use of classi cation accuracy to compare classi ers on natural data sets, providing a thorough investigation using ROC analysis, standard machine learnin...
Foster J. Provost, Tom Fawcett, Ron Kohavi