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» On the Complexity of Function Learning
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95
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ICML
2009
IEEE
16 years 1 months ago
Efficient Euclidean projections in linear time
We consider the problem of computing the Euclidean projection of a vector of length n onto a closed convex set including the 1 ball and the specialized polyhedra employed in (Shal...
Jun Liu, Jieping Ye
ML
2002
ACM
100views Machine Learning» more  ML 2002»
15 years 4 days ago
Structure in the Space of Value Functions
Solving in an efficient manner many different optimal control tasks within the same underlying environment requires decomposing the environment into its computationally elemental ...
David J. Foster, Peter Dayan
100
Voted
FOCI
2007
IEEE
15 years 6 months ago
Opposite Transfer Functions and Backpropagation Through Time
— Backpropagation through time is a very popular discrete-time recurrent neural network training algorithm. However, the computational time associated with the learning process t...
Mario Ventresca, Hamid R. Tizhoosh
IJCNN
2006
IEEE
15 years 6 months ago
Improving the Convergence of Backpropagation by Opposite Transfer Functions
—The backpropagation algorithm is a very popular approach to learning in feed-forward multi-layer perceptron networks. However, in many scenarios the time required to adequately ...
Mario Ventresca, Hamid R. Tizhoosh
117
Voted
ISNN
2005
Springer
15 years 6 months ago
FPGA Realization of a Radial Basis Function Based Nonlinear Channel Equalizer
In this paper we propose a radial basis function (RBF) neural network for nonlinear time-invariant channel equalizer. The RBF network model has a three-layer structure which is com...
Poyueh Chen, Hungming Tsai, ChengJian Lin, ChiYung...