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ICML
2009
IEEE
14 years 9 months ago
Multi-instance learning by treating instances as non-I.I.D. samples
Previous studies on multi-instance learning typically treated instances in the bags as independently and identically distributed. The instances in a bag, however, are rarely indep...
Zhi-Hua Zhou, Yu-Yin Sun, Yu-Feng Li
PKDD
2009
Springer
144views Data Mining» more  PKDD 2009»
14 years 3 months ago
Compositional Models for Reinforcement Learning
Abstract. Innovations such as optimistic exploration, function approximation, and hierarchical decomposition have helped scale reinforcement learning to more complex environments, ...
Nicholas K. Jong, Peter Stone
ICONIP
2007
13 years 10 months ago
RNN with a Recurrent Output Layer for Learning of Naturalness
– The behavior of recurrent neural networks with a recurrent output layer (ROL) is described mathematically and it is shown that using ROL is not only advantageous, but is in fac...
Ján Dolinský, Hideyuki Takagi
ECSCW
2003
13 years 10 months ago
Learning and Living in the 'New office'
‘Knowledge sharing’ and ‘learning’ are terms often connected with the ‘New office’, the “modern” open office space. Work in these settings becomes more and more dis...
Eva Bjerrum, Susanne Bødker
ATAL
2004
Springer
14 years 2 months ago
Bayesian Reinforcement Learning for Coalition Formation under Uncertainty
Research on coalition formation usually assumes the values of potential coalitions to be known with certainty. Furthermore, settings in which agents lack sufficient knowledge of ...
Georgios Chalkiadakis, Craig Boutilier