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» Analysis of Random Noise and Random Walk Algorithms
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BMCBI
2006
198views more  BMCBI 2006»
13 years 9 months ago
Gene selection and classification of microarray data using random forest
Background: Selection of relevant genes for sample classification is a common task in most gene expression studies, where researchers try to identify the smallest possible set of ...
Ramón Díaz-Uriarte, Sara Alvarez de ...
ICDAR
2007
IEEE
14 years 3 months ago
Handwritten Word Recognition Using Conditional Random Fields
The paper describes a lexicon driven approach for word recognition on handwritten documents using Conditional Random Fields(CRFs). CRFs are discriminative models and do not make a...
Shravya Shetty, Harish Srinivasan, Sargur N. Sriha...
SIGECOM
2006
ACM
184views ECommerce» more  SIGECOM 2006»
14 years 3 months ago
Computing pure nash equilibria in graphical games via markov random fields
We present a reduction from graphical games to Markov random fields so that pure Nash equilibria in the former can be found by statistical inference on the latter. Our result, wh...
Constantinos Daskalakis, Christos H. Papadimitriou
POPL
2003
ACM
14 years 9 months ago
Discovering affine equalities using random interpretation
We present a new polynomial-time randomized algorithm for discovering affine equalities involving variables in a program. The key idea of the algorithm is to execute a code fragme...
Sumit Gulwani, George C. Necula
STOC
2003
ACM
154views Algorithms» more  STOC 2003»
14 years 9 months ago
Boosting in the presence of noise
Boosting algorithms are procedures that "boost" low-accuracy weak learning algorithms to achieve arbitrarily high accuracy. Over the past decade boosting has been widely...
Adam Kalai, Rocco A. Servedio