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» Learning Algorithms for Domain Adaptation
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ILP
2000
Springer
15 years 6 months ago
Using ILP to Improve Planning in Hierarchical Reinforcement Learning
Hierarchical reinforcement learning has been proposed as a solution to the problem of scaling up reinforcement learning. The RLTOPs Hierarchical Reinforcement Learning System is an...
Mark D. Reid, Malcolm R. K. Ryan
IJCNN
2007
IEEE
15 years 9 months ago
Agnostic Learning vs. Prior Knowledge Challenge
We organized a challenge for IJCNN 2007 to assess the added value of prior domain knowledge in machine learning. Most commercial data mining programs accept data pre-formatted in ...
Isabelle Guyon, Amir Saffari, Gideon Dror, Gavin C...
NN
2008
Springer
152views Neural Networks» more  NN 2008»
15 years 2 months ago
Analysis of the IJCNN 2007 agnostic learning vs. prior knowledge challenge
We organized a challenge for IJCNN 2007 to assess the added value of prior domain knowledge in machine learning. Most commercial data mining programs accept data pre-formatted in ...
Isabelle Guyon, Amir Saffari, Gideon Dror, Gavin C...
INFOCOM
2003
IEEE
15 years 8 months ago
A Distributed and Adaptive Signal Processing Approach to Reducing Energy Consumption in Sensor Networks
— We propose a novel approach to reducing energy consumption in sensor networks using a distributed adaptive signal processing framework and efficient algorithm 1 . While the to...
Jim Chou, Dragan Petrovic, Kannan Ramchandran
NN
2002
Springer
15 years 2 months ago
Self-organizing maps with recursive neighborhood adaptation
Self-organizing maps (SOMs) are widely used in several fields of application, from neurobiology to multivariate data analysis. In that context, this paper presents variants of the...
John Aldo Lee, Michel Verleysen