Bor-yiing Su

Title: The Innovative Contributions of Bor-yiing Su in Machine Learning

Introduction: Bor-yiing Su is an accomplished inventor based in Mountain View, CA, known for her significant breakthrough in the field of machine learning techniques. As a member of the Google Inc. team, she has made substantial contributions that enhance the performance and scalability of machine learning systems.

Latest Patents: Bor-yiing Su holds a patent titled "Robust large-scale machine learning in the cloud." This innovative patent introduces a new scalable coordinate descent (SCD) algorithm designed for generalized linear models. The hallmark of Su's invention is its consistent convergence behavior, irrespective of the scaling of SCD or the computing environment utilized. This robustness allows the SCD algorithm to efficiently handle large datasets, even on cost-effective commodity servers. The patent emphasizes the parallel update mechanism by naturally partitioning parameters into blocks, which facilitates simultaneous updates without sacrificing convergence. Experimental results validating the cost-effectiveness and scalability of SCD were demonstrated using real advertising datasets.

Career Highlights: Throughout her career, Bor-yiing Su has excelled in her role at Google Inc., where she has played a pivotal part in advancing machine learning methodologies. Her work not only enriches the company's technological landscape but also pushes the boundaries of capabilities in processing large-scale datasets.

Collaborations: In her innovative pursuits, Bor-yiing Su has collaborated with notable colleagues, including Steffen Rendle and Dennis Craig Fetterly. These partnerships have fostered a creative environment that drives research and development in cutting-edge algorithms and technologies.

Conclusion: Bor-yiing Su's contributions to the field of machine learning exemplify the importance of innovation in technology. Her patented work on scalable algorithms not only addresses current challenges but also lays a foundation for future advancements in the industry. As she continues her journey at Google Inc., her impact on machine learning and data processing remains profound and inspiring.