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ICML
2006
IEEE
16 years 7 months ago
Cost-sensitive learning with conditional Markov networks
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...
Prithviraj Sen, Lise Getoor
GECCO
2009
Springer
188views Optimization» more  GECCO 2009»
15 years 10 months ago
Exploiting multiple classifier types with active learning
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...
Zhenyu Lu, Josh Bongard
CVPR
2009
IEEE
17 years 1 months ago
Learning Optimized MAP Estimates in Continuously-Valued MRF Models
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...
Kegan G. G. Samuel, Marshall F. Tappen
IROS
2008
IEEE
117views Robotics» more  IROS 2008»
16 years 1 months ago
Towards a cognitive robot that uses internal rehearsal to learn affordance relations
—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,...
ICDCSW
2006
IEEE
16 years 20 days ago
Improve Searching by Reinforcement Learning in Unstructured P2Ps
— 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...
Xiuqi Li, Jie Wu