Jianxin Liao

Title: Innovations of Jianxin Liao

Introduction

Jianxin Liao is a prominent inventor based in Beijing, China. He has made significant contributions to the field of deep learning and task scheduling. With a total of five patents to his name, Liao's work focuses on enhancing the efficiency of neural networks and optimizing task management through advanced methodologies.

Latest Patents

Liao's latest patents include a "Method and apparatus for task scheduling based on deep reinforcement learning." This invention outlines a process for obtaining multiple target subtasks and building corresponding target state data. The method utilizes a pre-trained task scheduling model to determine the optimal scheduling for each subtask. Another notable patent is the "Method and apparatus for accelerating distributed training of a deep neural network." This invention describes a distributed training mode that divides a deep neural network into sub-networks and utilizes a cluster architecture to improve training efficiency and reduce delays.

Career Highlights

Jianxin Liao is affiliated with the Beijing University of Posts and Telecommunications. His work at the university has allowed him to explore innovative solutions in the realm of artificial intelligence and machine learning. Liao's research has garnered attention for its practical applications in various industries.

Collaborations

Liao has collaborated with notable colleagues, including Jing Wang and Qi Qi. Their combined expertise has contributed to the advancement of research in deep learning and task scheduling.

Conclusion

Jianxin Liao's contributions to the field of deep learning and task scheduling are noteworthy. His innovative patents reflect a commitment to improving technology and efficiency in complex systems.