Michael J Cohen

Title: Michael J Cohen: Innovator in Machine Learning Data Amplification

Introduction

Michael J Cohen is a notable inventor based in Flushing, NY (US). He has made significant contributions to the field of machine learning, particularly in the area of data amplification. With a total of 3 patents to his name, Cohen's work is paving the way for advancements in artificial intelligence.

Latest Patents

Cohen's latest patent focuses on the amplification of initial training data. This innovation involves techniques that increase the amount of training data available to machine learning algorithms. A computer system can access an initial set of training data that specifies a plurality of sequences, each defining a set of data values. The system amplifies this initial set to create a revised set of training data. The amplification process includes identifying sub-sequences of data values within the initial sequences and employing an inheritance algorithm to generate additional sequences. Each of these new sequences may incorporate sub-sequences from at least two different sequences in the initial data set. The computer system then processes these additional sequences using a machine learning algorithm to train a machine learning model.

Career Highlights

Cohen is currently employed at CA, Inc., where he continues to develop innovative solutions in the realm of technology. His work has garnered attention for its potential to enhance machine learning capabilities and improve data processing efficiency.

Collaborations

Throughout his career, Cohen has collaborated with notable colleagues, including Daniel David Sill and William J McAllister. These partnerships have contributed to the advancement of his projects and the overall success of his innovations.

Conclusion

Michael J Cohen stands out as a key figure in the field of machine learning, with his patents reflecting a commitment to enhancing data utilization. His contributions are likely to have a lasting impact on the industry.