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Financial Problems tractable to Machine Learning Methods

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If you have a question about this talk, please contact Konstantina Palla.

Financial data provides a rich field for application of machine learning methods. Machine Learning theory can provide principled ways of extracting signal, making predictions, deciding actions, optimizing execution of actions, and understanding impact of action for financial data.

I will give an overview of the financial landscape, with problem setups, standard methods, as well as machine learning improvements on current methods where available.

The RCC will be tutorial in nature and thus there is no required reading.

This talk is part of the Machine Learning Reading Group @ CUED series.

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