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AAAI
2010
13 years 9 months ago
Adaptive Transfer Learning
Transfer learning aims at reusing the knowledge in some source tasks to improve the learning of a target task. Many transfer learning methods assume that the source tasks and the ...
Bin Cao, Sinno Jialin Pan, Yu Zhang, Dit-Yan Yeung...
JMLR
2010
129views more  JMLR 2010»
13 years 2 months ago
Efficient Multioutput Gaussian Processes through Variational Inducing Kernels
Interest in multioutput kernel methods is increasing, whether under the guise of multitask learning, multisensor networks or structured output data. From the Gaussian process pers...
Mauricio Alvarez, David Luengo, Michalis Titsias, ...
TKDE
2010
137views more  TKDE 2010»
13 years 6 months ago
A Survey on Transfer Learning
—A major assumption in many machine learning and data mining algorithms is that the training and future data must be in the same feature space and have the same distribution. How...
Sinno Jialin Pan, Qiang Yang
ML
2010
ACM
135views Machine Learning» more  ML 2010»
13 years 2 months ago
Multi-domain learning by confidence-weighted parameter combination
State-of-the-art statistical NLP systems for a variety of tasks learn from labeled training data that is often domain specific. However, there may be multiple domains or sources o...
Mark Dredze, Alex Kulesza, Koby Crammer

Publication
233views
12 years 6 months ago
Sparse reward processes
We introduce a class of learning problems where the agent is presented with a series of tasks. Intuitively, if there is relation among those tasks, then the information gained duri...
Christos Dimitrakakis