Michael Bowling

Title: Michael Bowling: Innovator in Predictive Systems

Introduction

Michael Bowling is a prominent inventor based in Edmonton, Canada. He is known for his contributions to the field of predictive systems, particularly through his innovative patent that addresses significant challenges in conventional prediction methods.

Latest Patents

Michael Bowling holds a patent titled "Method and system for predicting discrete sequences using deep context tree weighting." This patent describes systems and methods that utilize deep, convolutional neural networks over exponentially long history windows to learn alphabets for context tree weighting (CTW) for prediction. The invention effectively addresses known issues of depth and breadth in conventional context tree weighting predictions. To manage depth, the history can be segmented into time windows, allowing for the ability to look back exponentially far while using less information the further one looks back. To tackle breadth, a deep neural network classifier is employed to learn how to map arbitrary length histories to a small output symbol alphabet. The sequence of symbols produced by this classifier over the history windows serves as the input sequence to CTW.

Career Highlights

Throughout his career, Michael Bowling has worked with notable companies, including Sony Group Corporation and Sony Corporation of America. His experience in these organizations has contributed to his expertise in developing advanced predictive systems.

Collaborations

Michael has collaborated with esteemed colleagues such as Satinder Singh Baveja and Peter R Wurman. These collaborations have further enriched his work and innovations in the field.

Conclusion

Michael Bowling is a significant figure in the realm of predictive systems, with a focus on enhancing the accuracy and efficiency of predictions through innovative methodologies. His contributions continue to influence the field and inspire future advancements.