Daniel L K Yamins

Title: Innovations of Daniel L K Yamins

Introduction

Daniel L K Yamins is an accomplished inventor based in Sunnyvale, CA. He has made significant contributions to the field of neural networks, particularly in the area of pruning techniques. His innovative approach aims to enhance the efficiency of neural networks during both training and testing phases.

Latest Patents

Yamins holds a patent for a system and method for pruning neural networks at initialization using iteratively conserving synaptic flow. This method allows for the pruning of parameters in a neural network at initialization, which saves time, memory, and energy. The result is a highly sparse trainable subnetwork that does not require training or data input, making it a data-agnostic pruning system. The method preserves the total flow of synaptic strengths through the network while adhering to a sparsity constraint.

Career Highlights

Throughout his career, Daniel has worked with notable organizations such as NTT Research, Inc. and Leland Stanford Junior University. His work has focused on advancing the capabilities of neural networks and improving their efficiency.

Collaborations

Yamins has collaborated with talented individuals in his field, including Hidenori Tanaka and Daniel Kunin. These collaborations have contributed to the development of innovative solutions in neural network technology.

Conclusion

Daniel L K Yamins is a pioneering inventor whose work in neural network pruning has the potential to revolutionize the field. His contributions reflect a commitment to enhancing the efficiency and effectiveness of artificial intelligence systems.