Alexander Rosenberg Johansen

Title: Innovations of Alexander Rosenberg Johansen

Introduction

Alexander Rosenberg Johansen is an accomplished inventor based in San Francisco, CA. He holds three patents that showcase his expertise in natural language processing and deep learning technologies. His innovative approaches have contributed significantly to advancements in the field.

Latest Patents

Johansen's latest patents include a deep neural network-based decision network and a probability-based guider. The deep neural network-based decision network proposes a combination of a computationally cheap, less-accurate bag of words (BoW) model and a computationally expensive, more-accurate long short-term memory (LSTM) model for natural processing tasks such as sentiment analysis. The BoW model is referred to as 'skimming', while the LSTM model is referred to as 'reading'. The probability-based guider (PBG) utilizes a probability thresholding strategy to determine whether to invoke the LSTM model based on the results of the BoW model. This technology aims to reliably classify sentences as positive or negative by learning the relationship between the two models.

Career Highlights

Throughout his career, Johansen has worked with notable companies such as Salesforce.com, Inc. and Salesforce, Inc. His experience in these organizations has allowed him to refine his skills and contribute to significant projects in the tech industry.

Collaborations

Some of his coworkers include Bryan McCann and James Bradbury. Their collaboration has likely fostered an environment of innovation and creativity in their respective projects.

Conclusion

Alexander Rosenberg Johansen is a notable inventor whose work in natural language processing and deep learning continues to influence the industry. His patents reflect a commitment to advancing technology and improving the way machines understand human language.