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AI
2002
Springer
13 years 7 months ago
Programming backgammon using self-teaching neural nets
TD-Gammon is a neural network that is able to teach itself to play backgammon solely by playing against itself and learning from the results. Starting from random initial play, TD...
Gerald Tesauro
ECIR
2009
Springer
14 years 5 months ago
Active Sampling for Rank Learning via Optimizing the Area under the ROC Curve
Abstract. Learning ranking functions is crucial for solving many problems, ranging from document retrieval to building recommendation systems based on an individual user’s prefer...
Pinar Donmez, Jaime G. Carbonell
NIPS
2008
13 years 9 months ago
Human Active Learning
We investigate a topic at the interface of machine learning and cognitive science. Human active learning, where learners can actively query the world for information, is contraste...
Rui M. Castro, Charles Kalish, Robert Nowak, Ruich...
TEC
2008
135views more  TEC 2008»
13 years 7 months ago
Evolving Output Codes for Multiclass Problems
In this paper, we propose an evolutionary approach to the design of output codes for multiclass pattern recognition problems. This approach has the advantage of taking into account...
Nicolás García-Pedrajas, Colin Fyfe
ECTEL
2007
Springer
14 years 2 months ago
An Interoperability Infrastructure for Distributed Feed Networks
Blogs have the aordance to become an integral part of teaching and learning processes as a vehicle for knowledge management. Open, exible systems integrating blogs provide user-f...
Fridolin Wild, Steinn E. Sigurðarson, Stefan S...