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105
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CORR
2006
Springer
111views Education» more  CORR 2006»
15 years 2 months ago
An associative memory for the on-line recognition and prediction of temporal sequences
This paper presents the design of an associative memory with feedback that is capable of on-line temporal sequence learning. A framework for on-line sequence learning has been prop...
Joy Bose, Stephen B. Furber, Jonathan L. Shapiro
CORR
2002
Springer
79views Education» more  CORR 2002»
15 years 2 months ago
Technical Note: Bias and the Quantification of Stability
Research on bias in machine learning algorithms has generally been concerned with the impact of bias on predictive accuracy. We believe that there are other factors that should al...
Peter D. Turney
148
Voted
SDM
2012
SIAM
216views Data Mining» more  SDM 2012»
13 years 5 months ago
Feature Selection "Tomography" - Illustrating that Optimal Feature Filtering is Hopelessly Ungeneralizable
:  Feature Selection “Tomography” - Illustrating that Optimal Feature Filtering is Hopelessly Ungeneralizable George Forman HP Laboratories HPL-2010-19R1 Feature selection; ...
George Forman
FLAIRS
2004
15 years 4 months ago
The Optimality of Naive Bayes
Naive Bayes is one of the most efficient and effective inductive learning algorithms for machine learning and data mining. Its competitive performance in classification is surpris...
Harry Zhang
126
Voted
ICML
2009
IEEE
16 years 3 months ago
Incorporating domain knowledge into topic modeling via Dirichlet Forest priors
Users of topic modeling methods often have knowledge about the composition of words that should have high or low probability in various topics. We incorporate such domain knowledg...
David Andrzejewski, Xiaojin Zhu, Mark Craven