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ICONIP
2009
13 years 5 months ago
Learning Gaussian Process Models from Uncertain Data
It is generally assumed in the traditional formulation of supervised learning that only the outputs data are uncertain. However, this assumption might be too strong for some learni...
Patrick Dallaire, Camille Besse, Brahim Chaib-draa
ICMLA
2009
13 years 5 months ago
The Neuro Slot Car Racer: Reinforcement Learning in a Real World Setting
This paper describes a novel real-world reinforcement learning application: The Neuro Slot Car Racer. In addition to presenting the system and first results based on Neural Fitted...
Tim C. Kietzmann, Martin Riedmiller
ILP
2001
Springer
13 years 12 months ago
Learning Functions from Imperfect Positive Data
The Bayesian framework of learning from positive noise-free examples derived by Muggleton [12] is extended to learning functional hypotheses from positive examples containing norma...
Filip Zelezný
AAAI
2006
13 years 9 months ago
Value-Function-Based Transfer for Reinforcement Learning Using Structure Mapping
Transfer learning concerns applying knowledge learned in one task (the source) to improve learning another related task (the target). In this paper, we use structure mapping, a ps...
Yaxin Liu, Peter Stone
ICPR
2008
IEEE
14 years 2 months ago
Learning polynomial function based neutral-emotion GMM transformation for emotional speaker recognition
One of the biggest challenges in speaker recognition is dealing with speaker-emotion variability. The basic problem is how to train the emotion GMMs of the speakers from their neu...
Zhenyu Shan, Yingchun Yang