Karan Singhal

Title: Karan Singhal: Innovator in Federated Learning

Introduction

Karan Singhal is a notable inventor based in Roslyn, NY (US). He has made significant contributions to the field of machine learning, particularly in the area of federated learning. His innovative approach has the potential to enhance the efficiency and effectiveness of machine learning models.

Latest Patents

Karan Singhal holds a patent for "Partially local federated learning." This patent encompasses methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a machine learning model with a set of local model parameters and a set of global model parameters under a partially local federated learning framework. The patent outlines a method that includes maintaining local data and data defining the local model parameters. It also involves receiving data that defines current values of the global model parameters and determining, based on the local data and current values, the local model parameters. Furthermore, it details how to generate parameter update data and transmit this data to update the global model parameters.

Career Highlights

Karan Singhal is currently employed at Google Inc., where he continues to work on innovative projects in machine learning. His expertise in federated learning positions him as a valuable asset in the tech industry.

Collaborations

Karan collaborates with talented individuals such as Hakim Sidahmed, Jr. and Zachary Alan Garrett. Their combined efforts contribute to advancing the field of machine learning and developing cutting-edge technologies.

Conclusion

Karan Singhal's work in federated learning exemplifies the innovative spirit of modern technology. His contributions are paving the way for more efficient machine learning applications, and his ongoing work at Google Inc. promises to yield further advancements in this exciting field.