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ATAL
2005
Springer
15 years 12 months ago
Improving reinforcement learning function approximators via neuroevolution
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Shimon Whiteson
COLT
2006
Springer
15 years 10 months ago
Efficient Learning Algorithms Yield Circuit Lower Bounds
We describe a new approach for understanding the difficulty of designing efficient learning algorithms. We prove that the existence of an efficient learning algorithm for a circui...
Lance Fortnow, Adam R. Klivans
NN
2008
Springer
143views Neural Networks» more  NN 2008»
15 years 6 months ago
A batch ensemble approach to active learning with model selection
Optimally designing the location of training input points (active learning) and choosing the best model (model selection) are two important components of supervised learning and h...
Masashi Sugiyama, Neil Rubens
ICML
2008
IEEE
16 years 7 months ago
Causal modelling combining instantaneous and lagged effects: an identifiable model based on non-Gaussianity
Causal analysis of continuous-valued variables typically uses either autoregressive models or linear Gaussian Bayesian networks with instantaneous effects. Estimation of Gaussian ...
Aapo Hyvärinen, Patrik O. Hoyer, Shohei Shimi...
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ICYCS
2008
IEEE
16 years 22 days ago
The Practice of Remote Education on Information Security
With the rapid development of computer science, its education mode also changes a lot. Teaching and learning are not restricted by the physical distance with the help of the netwo...
Wei Hu, Gang Wang, Qingsong Shi, Tianzhou Chen