Javid Ebrahimi

Title: Innovations by Javid Ebrahimi

Introduction

Javid Ebrahimi is an accomplished inventor based in Mountain View, CA. He has made significant contributions to the field of machine learning and natural language processing. With a total of three patents to his name, Ebrahimi is recognized for his innovative approaches to reducing biases in datasets and enhancing recommendation systems.

Latest Patents

One of Ebrahimi's latest patents is titled "System, method, and computer program product for reducing dataset biases in natural language inference tasks using unadversarial training." This invention provides systems for generating a machine learning model for classification tasks using unadversarial training. The process involves a processor that performs an unadversarial training procedure to train a machine learning model. The procedure includes receiving a training dataset, generating a noise vector, perturbing training samples, obtaining a gradient, and updating model weights to provide a trained machine learning model.

Another notable patent is focused on "Methods and systems for graph-based cross-domain restaurant recommendation." This method accesses transaction data related to restaurants across various locations. It determines the number of co-visitors shared by restaurants and generates a graphical representation based on this data. The graphical representation is transformed into restaurant embeddings, which are then used by a neural network model to generate restaurant preferences.

Career Highlights

Ebrahimi is currently employed at Visa International Service Association, where he applies his expertise in machine learning and data analysis. His work has contributed to advancements in financial technology and customer experience.

Collaborations

Some of Ebrahimi's notable coworkers include Wei Zhang and Xiaobo Dong, who collaborate with him on various projects within the company.

Conclusion

Javid Ebrahimi's innovative patents and contributions to machine learning demonstrate his commitment to advancing technology. His work continues to influence the fields of natural language processing and recommendation systems.