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A Distribution-Free Theory of Nonparametric Regression
Why is Nonparametric Regression Important? * How to Construct Nonparametric Regression Estimates * Lower Bounds * Partitioning Estimates * Kernel Estimates * k-NN Estimates * Splitting the Sample *Expand
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A Distribution-Free Theory of Nonparametric Regression (Springer Series in Statistics)
In undergoing this life, many people always try to do and get the best. New knowledge, experience, lesson, and everything that can improve the life will be done. However, many people sometimes feelExpand
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Stochastic approximation and optimization of random systems
I Foundations of stochastic approximation.- 1 Almost sure convergence of stochastic approximation procedures.- 2 Recursive methods for linear problems.- 3 Stochastic optimization under stochasticExpand
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Nonparametric nearest neighbor based empirical portfolio selection strategies
TLDR
In recent years optimal portfolio selection strategies for sequential investment have been shown to exist. Expand
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On the Averaged Stochastic Approximation for Linear Regression
For a linear regression function the average of stochastic approximation with constant gain is considered. In case of ergodic observations almost sure convergence is proved, where the limit is biasedExpand
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Rates of convergence for partitioning and nearest neighbor regression estimates with unbounded data
Estimation of regression functions from independent and identically distributed data is considered. The L"2 error with integration with respect to the design measure is used as an error criterion.Expand
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Rate of Convergence of $k$-Nearest-Neighbor Classification Rule
TLDR
We present the rate of convergence of the k-nearestneighbor classification rule according to the error probability of the Bayes decision for the corresponding nearest neighbor regression estimate. Expand
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Optimal global rates of convergence for nonparametric regression with unbounded data
Abstract Estimation of regression functions from independent and identically distributed data is considered. The L 2 error with integration with respect to the design measure is used as an errorExpand
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Machine Learning for Financial Engineering
On the History of the Growth Optimal Portfolio (M M Christensen) Empirical Log-Optimal Portfolio Selections: A Survey (L Gyorfi et al.) Log-Optimal Portfolio Selection with Proportional TransactionExpand
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