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» Adaptive Transfer Learning
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114
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CVPR
2011
IEEE
14 years 5 months ago
What You Saw is Not What You Get: Domain Adaptation Using Asymmetric Kernel Transforms
In real-world applications, “what you saw” during training is often not “what you get” during deployment: the distribution and even the type and dimensionality of features...
Brian Kulis, Kate Saenko, Trevor Darrell
KDD
2009
ACM
230views Data Mining» more  KDD 2009»
15 years 10 months ago
Cross domain distribution adaptation via kernel mapping
When labeled examples are limited and difficult to obtain, transfer learning employs knowledge from a source domain to improve learning accuracy in the target domain. However, the...
ErHeng Zhong, Wei Fan, Jing Peng, Kun Zhang, Jiang...
IJCAI
2007
14 years 11 months ago
Transfer Learning in Real-Time Strategy Games Using Hybrid CBR/RL
The goal of transfer learning is to use the knowledge acquired in a set of source tasks to improve performance in a related but previously unseen target task. In this paper, we pr...
Manu Sharma, Michael P. Holmes, Juan Carlos Santam...
78
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SLOGICA
2008
120views more  SLOGICA 2008»
14 years 9 months ago
Emergence of Information Transfer by Inductive Learning
We study a simple game theoretic model of information transfer which we consider to be a baseline model for capturing strategic aspects of epistemological questions. In particular,...
Simon M. Huttegger, Brian Skyrms
ILP
2007
Springer
15 years 3 months ago
Learning Relational Options for Inductive Transfer in Relational Reinforcement Learning
In reinforcement learning problems, an agent has the task of learning a good or optimal strategy from interaction with his environment. At the start of the learning task, the agent...
Tom Croonenborghs, Kurt Driessens, Maurice Bruynoo...