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» Models of active learning in group-structured state spaces
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ICML
2003
IEEE
16 years 5 months ago
Bayes Meets Bellman: The Gaussian Process Approach to Temporal Difference Learning
We present a novel Bayesian approach to the problem of value function estimation in continuous state spaces. We define a probabilistic generative model for the value function by i...
Yaakov Engel, Shie Mannor, Ron Meir
IJISTA
2007
124views more  IJISTA 2007»
15 years 4 months ago
Incremental learning for spoken affect classification and its application in call-centres
: This paper introduces a system for real-time incremental learning in a call-centre environment. The classifier used is a Support Vector Machine (SVM) and it is applied to telepho...
Donn Morrison, Ruili Wang, W. L. Xu, Liyanage C. D...
136
Voted
ATAL
2010
Springer
15 years 5 months ago
Linear options
Learning, planning, and representing knowledge in large state t multiple levels of temporal abstraction are key, long-standing challenges for building flexible autonomous agents. ...
Jonathan Sorg, Satinder P. Singh
125
Voted
ECMDAFA
2006
Springer
136views Hardware» more  ECMDAFA 2006»
15 years 8 months ago
Finding a Path to Model Consistency
A core problem in Model Driven Engineering is model consistency achievement: all models must satisfy relationships constraining them. Active consistency techniques monitor and cont...
Gregory de Fombelle, Xavier Blanc, Laurent Rioux, ...
ECCV
2010
Springer
15 years 9 months ago
Efficient Highly Over-Complete Sparse Coding using a Mixture Model
Sparse coding of sensory data has recently attracted notable attention in research of learning useful features from the unlabeled data. Empirical studies show that mapping the data...