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» Boosting for transfer learning
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FOCI
2007
IEEE
15 years 4 months ago
Opposite Transfer Functions and Backpropagation Through Time
— Backpropagation through time is a very popular discrete-time recurrent neural network training algorithm. However, the computational time associated with the learning process t...
Mario Ventresca, Hamid R. Tizhoosh
IJCNN
2006
IEEE
15 years 3 months ago
Improving the Convergence of Backpropagation by Opposite Transfer Functions
—The backpropagation algorithm is a very popular approach to learning in feed-forward multi-layer perceptron networks. However, in many scenarios the time required to adequately ...
Mario Ventresca, Hamid R. Tizhoosh
ICRA
2006
IEEE
110views Robotics» more  ICRA 2006»
15 years 3 months ago
Transfer of Learning for Complex Task Domains: a Demonstration using Multiple Robots
— This paper demonstrates a learning mechanism for complex tasks. Such tasks may be inherently expensive to learn in terms of training time and/or cost of obtaining each training...
Sameer Singh, Julie A. Adams
AAAI
2006
14 years 11 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»
14 years 8 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...