Alice Horan

Title: Innovations of Alice Horan in Machine Learning

Introduction

Alice Horan is an accomplished inventor based in Redmond, WA (US). She has made significant contributions to the field of machine learning, particularly in modeling causation. Her innovative approach has garnered attention in the tech community, showcasing her expertise and creativity.

Latest Patents

Alice Horan holds a patent for a method titled "Modelling causation in machine learning." This method involves sampling a temporal causal graph from a temporal graph distribution that specifies probabilities of directed causal edges between different variables of a feature vector at a present time step. It also considers the relationship between one variable at a preceding time step and another variable at the present time step. The process identifies a present parent, which is a cause of the selected variable in the present time step, and a preceding parent, which is a cause of the selected variable from the preceding time step. The method includes inputting values of each identified present and preceding parent into respective encoders, resulting in embeddings that are combined and input into a decoder to reconstruct the value of the selected variable. This innovative approach has the potential to enhance machine learning models significantly.

Career Highlights

Alice Horan is currently employed at Microsoft Technology Licensing, LLC, where she continues to develop her ideas and contribute to advancements in technology. Her work at Microsoft has allowed her to collaborate with other talented individuals in the field, further enhancing her skills and knowledge.

Collaborations

Alice has worked alongside notable colleagues such as Wenbo Gong and Cheng Zhang. Their collaborative efforts have contributed to the development of innovative solutions in machine learning.

Conclusion

Alice Horan's contributions to machine learning through her patent and work at Microsoft Technology Licensing, LLC, highlight her role as a leading inventor in the field. Her innovative methods for modeling causation are paving the way for future advancements in technology.