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» Transfer Learning and Intelligence: an Argument and Approach
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FLAIRS
2007
13 years 10 months ago
Context-Sensitive MTL Networks for Machine Lifelong Learning
Context-sensitive Multiple Task Learning, or csMTL, is presented as a method of inductive transfer that uses a single output neural network and additional contextual inputs for le...
Daniel L. Silver, Ryan Poirier
GECCO
2007
Springer
178views Optimization» more  GECCO 2007»
14 years 1 months ago
Coevolution of intelligent agents using cartesian genetic programming
A coevolutionary competitive learning environment for two antagonistic agents is presented. The agents are controlled by a new kind of computational network based on a compartment...
Gul Muhammad Khan, Julian Francis Miller, David M....
AAAI
2008
13 years 10 months ago
Text Categorization with Knowledge Transfer from Heterogeneous Data Sources
Multi-category classification of short dialogues is a common task performed by humans. When assigning a question to an expert, a customer service operator tries to classify the cu...
Rakesh Gupta, Lev-Arie Ratinov
ICML
2007
IEEE
14 years 8 months ago
Learning a meta-level prior for feature relevance from multiple related tasks
In many prediction tasks, selecting relevant features is essential for achieving good generalization performance. Most feature selection algorithms consider all features to be a p...
Su-In Lee, Vassil Chatalbashev, David Vickrey, Dap...
ARGMAS
2007
Springer
13 years 11 months ago
Arguing and Explaining Classifications
Argumentation is a promising approach used by autonomous agents for reasoning about inconsistent knowledge, based on the construction and the comparison of arguments. In this pape...
Leila Amgoud, Mathieu Serrurier