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We provide a variable metric stochastic approximation theory.
A stochastic approximation method
H. E. Robbins and S. Monro · 1951
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Multidimensional stochastic approximation methods
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A convergence theorem for non negative almost supermartingales and some applications
H. E. Robbins and D. O. Siegmund · 1971
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Methods of Information Geometry
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Exponentiated gradient versus gradient descent for linear predictors
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Natural gradient works efficiently in learning
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Relative loss bounds for on-line density estimation with the exponential family of distributions
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A stochastic quasi-Newton method for online convex optimization
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Pegasos: Primal estimated sub-gradient solver for SVM
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Logarithmic regret algorithms for online convex optimization
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