Discovery through Machine Learning:
Computational Finance Program
Oregon Graduate Institute
Machine Learning algorithms have proven to be powerful tools for finding patterns in data and discovering solutions to difficult problems in a wide range of fields. In this presentation, I'll survey three styles of machine learning, focusing on key algorithms, and explaining why they are innovative and powerful. These include supervised learning (w/ multi-layer perceptrons), unsupervised learning (e.g. independent component analysis) and reinforcement learning. Benefits to these methods include bypassing Bellman's curse of dimensionality, discovering subtle or higher order statistical structures in data, and developing efficient strategies for making real-world decisions.
I'll describe application examples from several fields, time permitting, including computer games, signal processing, forecasting the U.S. economy and trading the global financial markets.
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