4591 search results - page 147 / 919 » Learning from Dyadic Data |
137
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COLT
1998
Springer
15 years 8 months ago
1998
Springer
Most of the work which attempts to give bounds on the generalization error of the hypothesis generated by a learning algorithm is based on methods from the theory of uniform conve...
128
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IJCAI
2001
15 years 5 months ago
2001
The task of causal structure discovery from empirical data is a fundamental problem in many areas. Experimental data is crucial for accomplishing this task. However, experiments a...
142
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NIPS
2000
15 years 5 months ago
2000
Bayesian networks are graphical representations of probability distributions. In virtually all of the work on learning these networks, the assumption is that we are presented with...
128
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IJCAI
1989
15 years 5 months ago
1989
Despite the fact that many symbolic and connectionist (neural net) learning algorithms are addressing the same problem of learning from classified examples, very little Is known r...
129
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ICML
2002
IEEE
16 years 4 months ago
2002
IEEE
Supervised learning techniques for text classi cation often require a large number of labeled examples to learn accurately. One way to reduce the amountoflabeled datarequired is t...