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ICML
2010
IEEE
15 years 5 months ago
Modeling Transfer Learning in Human Categorization with the Hierarchical Dirichlet Process
Transfer learning can be described as the tion of abstract knowledge from one learning domain or task and the reuse of that knowledge in a related domain or task. In categorizatio...
Kevin R. Canini, Mikhail M. Shashkov, Thomas L. Gr...
NIPS
2007
15 years 6 months ago
Multi-Task Learning via Conic Programming
When we have several related tasks, solving them simultaneously is shown to be more effective than solving them individually. This approach is called multi-task learning (MTL) and...
Tsuyoshi Kato, Hisashi Kashima, Masashi Sugiyama, ...
121
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ALT
2000
Springer
16 years 1 months ago
Learning Recursive Concepts with Anomalies
This paper provides a systematic study of inductive inference of indexable concept classes in learning scenarios in which the learner is successful if its final hypothesis describ...
Gunter Grieser, Steffen Lange, Thomas Zeugmann
ICML
2008
IEEE
16 years 5 months ago
Optimizing estimated loss reduction for active sampling in rank learning
Learning to rank is becoming an increasingly popular research area in machine learning. The ranking problem aims to induce an ordering or preference relations among a set of insta...
Pinar Donmez, Jaime G. Carbonell
AAAI
2007
15 years 7 months ago
Mapping and Revising Markov Logic Networks for Transfer Learning
Transfer learning addresses the problem of how to leverage knowledge acquired in a source domain to improve the accuracy and speed of learning in a related target domain. This pap...
Lilyana Mihalkova, Tuyen N. Huynh, Raymond J. Moon...