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Ledoit-Wolf linear shrinkage with unknown mean
When the mean is known, Ledoit and Wolf (2004) proposed a linear shrinkage estimator and proved its convergence under those asymptotics.
On some theoretical limitations of Generative Adversarial Networks
Generative Adversarial Networks have become a core technique in Machine Learning to generate unknown distributions from data samples.
Adversarial trading
Adversarial samples have drawn a lot of attention from the Machine Learning community in the past few years.
An empirical study of neural networks for trend detection in time series
Detecting structure in noisy time series is a difficult task.
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