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» Evaluating learning algorithms and classifiers
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ADBIS
2003
Springer
108views Database» more  ADBIS 2003»
15 years 9 months ago
Dynamic Integration of Classifiers in the Space of Principal Components
Recent research has shown the integration of multiple classifiers to be one of the most important directions in machine learning and data mining. It was shown that, for an ensemble...
Alexey Tsymbal, Mykola Pechenizkiy, Seppo Puuronen...
ICML
2010
IEEE
15 years 5 months ago
Multi-agent Learning Experiments on Repeated Matrix Games
This paper experimentally evaluates multiagent learning algorithms playing repeated matrix games to maximize their cumulative return. Previous works assessed that Qlearning surpas...
Bruno Bouzy, Marc Métivier
ICML
2008
IEEE
16 years 5 months ago
Training restricted Boltzmann machines using approximations to the likelihood gradient
A new algorithm for training Restricted Boltzmann Machines is introduced. The algorithm, named Persistent Contrastive Divergence, is different from the standard Contrastive Diverg...
Tijmen Tieleman
CORR
2010
Springer
128views Education» more  CORR 2010»
15 years 4 months ago
Sublinear Optimization for Machine Learning
Abstract--We give sublinear-time approximation algorithms for some optimization problems arising in machine learning, such as training linear classifiers and finding minimum enclos...
Kenneth L. Clarkson, Elad Hazan, David P. Woodruff
IWC
2008
99views more  IWC 2008»
15 years 4 months ago
Pedagogy and usability in interactive algorithm visualizations: Designing and evaluating CIspace
Interactive algorithm visualizations (AVs) are powerful tools for teaching and learning concepts that are difficult to describe with static media alone. However, while countless A...
Saleema Amershi, Giuseppe Carenini, Cristina Conat...