3 papers
cs.LG2021
On some theoretical limitations of Generative Adversarial Networks
Benoît Oriol, Alexandre Miot
Generative Adversarial Networks have become a core technique in Machine Learning to generate unknown distributions from data samples. They have been used in a wide range of context…
q-fin.TR2020
Adversarial trading
Alexandre Miot
Adversarial samples have drawn a lot of attention from the Machine Learning community in the past few years. An adverse sample is an artificial data point coming from an impercepti…
cs.LG2019
An empirical study of neural networks for trend detection in time series
Alexandre Miot, Gilles Drigout
Detecting structure in noisy time series is a difficult task. One intuitive feature is the notion of trend. From theoretical hints and using simulated time series, we empirically i…