3050 search results - page 134 / 610 » On-line Algorithms in Machine Learning |
146
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ECML
2006
Springer
15 years 5 months ago
2006
Springer
Abstract. This paper is about the evaluation of the results of clustering algorithms, and the comparison of such algorithms. We propose a new method based on the enrichment of a se...
133
Voted
ICML
2004
IEEE
16 years 4 months ago
2004
IEEE
The majority of the existing algorithms for learning decision trees are greedy--a tree is induced top-down, making locally optimal decisions at each node. In most cases, however, ...
138
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ICML
2007
IEEE
16 years 4 months ago
2007
IEEE
Reinforcement learning algorithms can become unstable when combined with linear function approximation. Algorithms that minimize the mean-square Bellman error are guaranteed to co...
140
Voted
ICML
2010
IEEE
15 years 1 months ago
2010
IEEE
Most learning to rank research has assumed that the utility of different documents is independent, which results in learned ranking functions that return redundant results. The fe...
125
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ICDM
2006
IEEE
15 years 9 months ago
2006
IEEE
In active learning, a machine learning algorithm is given an unlabeled set of examples U, and is allowed to request labels for a relatively small subset of U to use for training. ...