Patents by Inventor Venkatasatya Premnath AYYALASOMAYAJULA

Venkatasatya Premnath AYYALASOMAYAJULA has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20210232911
    Abstract: Techniques performed by a data processing system for analyzing training data for a machine learning model and identifying outliers in the training data herein include obtaining training data for the model from a memory of the data processing system; analyzing the training data using a Siamese Neural Network to determine within-label similarities and cross-label similarities associated with a plurality of data elements within the training data, the within-label representing similarities between a respective data element and a first set of data elements similarly labeled in the training data, the cross-label similarities representing similarities between the respective data element and a second set of data elements dissimilarly labeled in the training data; identifying outlier data elements in the plurality of data elements based on the within-label and cross-label similarities; and processing the training data comprising the outlier data elements.
    Type: Application
    Filed: January 28, 2020
    Publication date: July 29, 2021
    Inventors: Nishant VELAGAPUDI, Zhengwen ZHU, Venkatasatya Premnath AYYALASOMAYAJULA
  • Publication number: 20210232980
    Abstract: Techniques performed by a data processing system for analyzing the impact of training data changes on a machine learning model herein include training a first instance of a machine learning model with a first set of training data; modifying the first set of training data to produce a second set of training data; training a second instance of the model with the second set of training data; comparing the first instance of the model to the second instance of the model to determine features that differ between the first instance and the second instance of the model; identifying a subset of historical data associated with the features that differ between the first instance and the second instance of the model; and scoring the subset of the historical data to produce a report identifying differences in the output of the first instance and the second instance of the machine learning model.
    Type: Application
    Filed: January 28, 2020
    Publication date: July 29, 2021
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Nishant VELAGAPUDI, Zhengwen ZHU, Venkatasatya Premnath AYYALASOMAYAJULA, Rajkumar RAMASAMY