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» On Universal Transfer Learning
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AAAI
2006
13 years 10 months ago
Using Homomorphisms to Transfer Options across Continuous Reinforcement Learning Domains
We examine the problem of Transfer in Reinforcement Learning and present a method to utilize knowledge acquired in one Markov Decision Process (MDP) to bootstrap learning in a mor...
Vishal Soni, Satinder P. Singh
RAS
2010
131views more  RAS 2010»
13 years 6 months ago
Probabilistic Policy Reuse for inter-task transfer learning
Policy Reuse is a reinforcement learning technique that efficiently learns a new policy by using past similar learned policies. The Policy Reuse learner improves its exploration b...
Fernando Fernández, Javier García, M...
ICML
2009
IEEE
14 years 9 months ago
Deep transfer via second-order Markov logic
Standard inductive learning requires that training and test instances come from the same distribution. Transfer learning seeks to remove this restriction. In shallow transfer, tes...
Jesse Davis, Pedro Domingos
PAMI
2012
11 years 11 months ago
Domain Transfer Multiple Kernel Learning
—Cross-domain learning methods have shown promising results by leveraging labeled patterns from the auxiliary domain to learn a robust classifier for the target domain which has ...
Lixin Duan, Ivor W. Tsang, Dong Xu
MINENET
2005
ACM
14 years 2 months ago
Identifying BGP routing table transfers
BGP routing updates collected by monitoring projects such as RouteViews and RIPE have been a vital source to our understanding of the global routing system. The updates logged by ...
Beichuan Zhang, Vamsi Kambhampati, Mohit Lad, Dani...