Data Compression - Removing Noisy Data - Deeper Into Machine Learning

With machine learning receiving a significant amount of attention in finance, the UBS Global Quantitative research team wanted to recognize how deep learning, a related but more discerning aspect of artificial intelligence recognition, might benefit investors. To tackle the issue UBS called Matthew Dixon, Professor of Finance & Statistics at the Illinois Institute of Technology, to explain how very high dimensional input and hierarchical, data compression, multi-layer networks might benefit a stock portfolio. Dixon has experience working in the banking and high frequency trading in addition to holding a Ph.D. from the Imperial College London, all which points to the cutting edge of the cutting edge in computational finance. Get the entire 10-part series on Ray Dalio in PDF. Dixon had a primary goal in his conference call with UBS and their clients.