There has been a recent, growing interest in classification and link prediction in structured domains. Methods such as conditional random fields and relational Markov networks sup...
Many approaches to active learning involve training one classifier by periodically choosing new data points about which the classifier has the least confidence, but designing a co...
We present a new approach for the discriminative training
of continuous-valued Markov Random Field (MRF)
model parameters. In our approach we train the MRF
model by optimizing t...
—This paper introduces a new approach to develop robots that can learn general affordance relations from their experiences. Our approach is a part of larger efforts to develop a ...
Erdem Erdemir, Carl B. Frankel, Kazuhiko Kawamura,...
— Existing searching schemes in unstructured P2Ps can be categorized as either blind or informed. The quality of query results in blind schemes is low. Informed schemes use simpl...