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» Using Machine Learning to Focus Iterative Optimization
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120
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ICML
2010
IEEE
15 years 3 months ago
Convergence of Least Squares Temporal Difference Methods Under General Conditions
We consider approximate policy evaluation for finite state and action Markov decision processes (MDP) in the off-policy learning context and with the simulation-based least square...
Huizhen Yu
101
Voted
ML
2002
ACM
145views Machine Learning» more  ML 2002»
15 years 2 months ago
Boosting Methods for Regression
In this paper we examine ensemble methods for regression that leverage or "boost" base regressors by iteratively calling them on modified samples. The most successful lev...
Nigel Duffy, David P. Helmbold
115
Voted
ICALT
2005
IEEE
15 years 8 months ago
Integrating Wireless Technology in Pocket Electronic Dictionary to Enhance Language Learning
We believe that with regard to the information technology applications in education, one student one computing device will be the future and long-term trend. Many related studies ...
Jen-Kai Liang, Tzu-Chien Liu, Hsue-Yie Wang, Tak-W...
ICML
2007
IEEE
16 years 3 months ago
Asymptotic Bayesian generalization error when training and test distributions are different
In supervised learning, we commonly assume that training and test data are sampled from the same distribution. However, this assumption can be violated in practice and then standa...
Keisuke Yamazaki, Klaus-Robert Müller, Masash...
114
Voted
FLAIRS
2003
15 years 4 months ago
Hybrid Intelligence for Driver Assistance
We report on our on-going effort to build an adaptive driver support system, Driver AdvocateTM , merging various AI techniques, in particular, agents, ontology, production systems...
Chung Hee Hwang, Noel Massey, Bradford W. Miller, ...