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» Approximation Methods for Supervised Learning
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117
Voted
ECML
2004
Springer
15 years 5 months ago
Convergence and Divergence in Standard and Averaging Reinforcement Learning
Although tabular reinforcement learning (RL) methods have been proved to converge to an optimal policy, the combination of particular conventional reinforcement learning techniques...
Marco Wiering
109
Voted
ICDM
2007
IEEE
129views Data Mining» more  ICDM 2007»
15 years 6 months ago
Semi-supervised Clustering Using Bayesian Regularization
Text clustering is most commonly treated as a fully automated task without user supervision. However, we can improve clustering performance using supervision in the form of pairwi...
Zuobing Xu, Ram Akella, Mike Ching, Renjie Tang
AUSDM
2007
Springer
102views Data Mining» more  AUSDM 2007»
15 years 4 months ago
A Two-Step Classification Approach to Unsupervised Record Linkage
Linking or matching databases is becoming increasingly important in many data mining projects, as linked data can contain information that is not available otherwise, or that woul...
Peter Christen
99
Voted
GECCO
2006
Springer
177views Optimization» more  GECCO 2006»
15 years 4 months ago
Hyper-ellipsoidal conditions in XCS: rotation, linear approximation, and solution structure
The learning classifier system XCS is an iterative rulelearning system that evolves rule structures based on gradient-based prediction and rule quality estimates. Besides classifi...
Martin V. Butz, Pier Luca Lanzi, Stewart W. Wilson
MICCAI
2006
Springer
16 years 1 months ago
Detection of Protrusions in Curved Folded Surfaces Applied to Automated Polyp Detection in CT Colonography
Over the past years many computer aided diagnosis (CAD) schemes have been presented for the detection of colonic polyps in CT Colonography. The vast majority of these methods (impl...
Cees van Wijk, Vincent Frans van Ravesteijn, Frans...