Chenjun Xiao

Title: Chenjun Xiao - Innovator in Machine Learning

Introduction

Chenjun Xiao is a notable inventor based in Edmonton, Canada. He has made significant contributions to the field of machine learning, particularly through his innovative patent. His work focuses on enhancing the efficiency and effectiveness of data structures used in controlling agents.

Latest Patents

Chenjun Xiao holds a patent titled "System and method for tree-based machine learning." This patent describes systems and methods for updating a multi-level data structure for controlling an agent. The method involves accessing a data structure that defines one or more nodes. A non-leaf node may be associated with one or more edges for traversing to a subsequent node. Each edge may have a visit count and a softmax state-action value estimation. The method identifies a node trajectory based on an asymptotically converging sampling policy, which includes a root node and a leaf node. It also determines a reward indication associated with the node trajectory and updates the visit count and softmax state-action value estimate for at least one non-leaf node based on the determined reward indication. Chenjun Xiao has 1 patent to his name.

Career Highlights

Chenjun Xiao is currently employed at the Royal Bank of Canada, where he applies his expertise in machine learning to develop innovative solutions. His work at the bank allows him to leverage his skills in a practical environment, contributing to advancements in financial technology.

Collaborations

One of his notable collaborators is Ruitong Huang. Together, they work on projects that push the boundaries of machine learning applications.

Conclusion

Chenjun Xiao is a prominent figure in the field of machine learning, with a focus on improving data structures for agent control. His contributions through his patent and work at the Royal Bank of Canada highlight his commitment to innovation in technology.