3076 search results - page 36 / 616 » Active Learning for Networked Data |
131
Voted
NIPS
2007
15 years 4 months ago
2007
Active learning sequentially selects unlabeled instances to label with the goal of reducing the effort needed to learn a good classifier. Most previous studies in active learning...
123
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ICANN
2007
Springer
15 years 6 months ago
2007
Springer
Meta-Learning has been used to select algorithms based on the features of the problems being tackled. Each training example in this context, i.e. each meta-example, stores the feat...
107
Voted
IJCNN
2007
IEEE
15 years 9 months ago
2007
IEEE
— In this paper a clustering algorithm that learns the groups of synchronized spike trains directly from data is proposed. Clustering of spike trains based on the presence of syn...
134
Voted
PR
2007
15 years 2 months ago
2007
In relevance feedback algorithms, selective sampling is often used to reduce the cost of labeling and explore the unlabeled data. In this paper, we proposed an active learning alg...
134
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HYBRID
1998
Springer
15 years 6 months ago
1998
Springer
We discuss properties of high order neurons in competitive learning. In such neurons, geometric shapes replace the role of classic `point' neurons in neural networks. Complex ...