Bernard Freund

Title: The Innovations of Bernard Freund

Introduction

Bernard Freund is a notable inventor based in Victoria, Canada. He has made significant contributions to the field of neural networks and feature engineering. With a total of 4 patents to his name, Freund's work has advanced the understanding and optimization of neural networks.

Latest Patents

One of Freund's latest patents focuses on feature engineering in neural networks optimization. In this innovation, a transitive closure data structure is constructed for a pair of features represented in a vector space corresponding to an input dataset. The data structure includes a set of entries corresponding to all possible paths between the first and second features in a graph of the vector space. The data structure is then reduced by removing a subset of entries, ensuring that only a single entry corresponding to a single path remains in the transitive closure data structure. A feature cross is formed from a cluster of features remaining in a reduced ontology graph resulting from this reduction. A layer is configured in a neural network to represent the feature cross, which enables the neural network to produce predictions that are within a defined accuracy relative to the dataset.

Career Highlights

Throughout his career, Bernard Freund has worked with prominent companies such as IBM and Kyndryl, Inc. His experience in these organizations has allowed him to collaborate on various innovative projects and contribute to advancements in technology.

Collaborations

Freund has had the opportunity to work alongside talented individuals, including Mary E. Rudden and Dennis Anthony Perpetua, Jr. These collaborations have enriched his professional journey and fostered a creative environment for innovation.

Conclusion

Bernard Freund's contributions to the field of neural networks and feature engineering demonstrate his commitment to innovation. His patents reflect a deep understanding of complex data structures and their applications in technology.