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» Learning Functions from Imperfect Positive Data
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BMCBI
2006
134views more  BMCBI 2006»
13 years 10 months ago
Application of machine learning in SNP discovery
Background: Single nucleotide polymorphisms (SNP) constitute more than 90% of the genetic variation, and hence can account for most trait differences among individuals in a given ...
Lakshmi K. Matukumalli, John J. Grefenstette, Davi...
COLT
2010
Springer
13 years 8 months ago
Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
We present a new family of subgradient methods that dynamically incorporate knowledge of the geometry of the data observed in earlier iterations to perform more informative gradie...
John Duchi, Elad Hazan, Yoram Singer
ALT
2006
Springer
14 years 7 months ago
Probabilistic Generalization of Simple Grammars and Its Application to Reinforcement Learning
Abstract. Recently, some non-regular subclasses of context-free grammars have been found to be efficiently learnable from positive data. In order to use these efficient algorithms ...
Takeshi Shibata, Ryo Yoshinaka, Takashi Chikayama
KDD
2008
ACM
161views Data Mining» more  KDD 2008»
14 years 10 months ago
Spectral domain-transfer learning
Traditional spectral classification has been proved to be effective in dealing with both labeled and unlabeled data when these data are from the same domain. In many real world ap...
Xiao Ling, Wenyuan Dai, Gui-Rong Xue, Qiang Yang, ...
ESANN
2008
13 years 11 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...