Patents by Inventor Andrea I. Martin

Andrea I. Martin 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).

  • Incident prediction and response using deep learning techniques and multimodal data
    Patent number: 11275990
    Abstract: In an approach to incident prediction and response, one or more computer processors receive one or more alerts corresponding to an incident. The one or more computer processors aggregate the one or more alerts with additional data corresponding to the incident. The one or more computer processors feed the aggregated data into a prediction model, where training of the prediction model uses associated independent stacked Restricted Boltzmann Machines utilizing one or more supervised methods and one or more unsupervised methods. The one or more computer processors determine, based, at least in part, on one or more calculations by the prediction model, at least one probability of the incident. The one or more computer processors determine whether the at least one probability exceeds a pre-defined threshold. In response to determining the at least one probability exceeds a pre-defined threshold, the one or more computer processors send at least one notification.
    Type: Grant
    Filed: February 14, 2019
    Date of Patent: March 15, 2022
    Assignee: International Business Machines Corporation
    Inventors: Aaron K. Baughman, Christian Eggenberger, Andrea I. Martin, Daniel S. Stoessel, Craig M. Trim
  • INCIDENT PREDICTION AND RESPONSE USING DEEP LEARNING TECHNIQUES AND MULTIMODAL DATA
    Publication number: 20190180172
    Abstract: In an approach to incident prediction and response, one or more computer processors receive one or more alerts corresponding to an incident. The one or more computer processors aggregate the one or more alerts with additional data corresponding to the incident. The one or more computer processors feed the aggregated data into a prediction model, where training of the prediction model uses associated independent stacked Restricted Boltzmann Machines utilizing one or more supervised methods and one or more unsupervised methods. The one or more computer processors determine, based, at least in part, on one or more calculations by the prediction model, at least one probability of the incident. The one or more computer processors determine whether the at least one probability exceeds a pre-defined threshold. In response to determining the at least one probability exceeds a pre-defined threshold, the one or more computer processors send at least one notification.
    Type: Application
    Filed: February 14, 2019
    Publication date: June 13, 2019
    Inventors: Aaron K. Baughman, Christian Eggenberger, Andrea I. Martin, Daniel S. Stoessel, Craig M. Trim
  • Incident prediction and response using deep learning techniques and multimodal data
    Patent number: 10289949
    Abstract: In an approach to incident prediction and response, one or more computer processors receive one or more alerts corresponding to an incident. The one or more computer processors aggregate the one or more alerts with additional data corresponding to the incident. The one or more computer processors feed the aggregated data into a prediction model, where training of the prediction model uses associated independent stacked Restricted Boltzmann Machines utilizing one or more supervised methods and one or more unsupervised methods. The one or more computer processors determine, based, at least in part, on one or more calculations by the prediction model, at least one probability of the incident. The one or more computer processors determine whether the at least one probability exceeds a pre-defined threshold. In response to determining the at least one probability exceeds a pre-defined threshold, the one or more computer processors send at least one notification.
    Type: Grant
    Filed: September 29, 2015
    Date of Patent: May 14, 2019
    Assignee: International Business Machines Corporation
    Inventors: Aaron K. Baughman, Christian Eggenberger, Andrea I. Martin, Daniel S. Stoessel, Craig M. Trim
  • INCIDENT PREDICTION AND RESPONSE USING DEEP LEARNING TECHNIQUES AND MULTIMODAL DATA
    Publication number: 20170091617
    Abstract: In an approach to incident prediction and response, one or more computer processors receive one or more alerts corresponding to an incident. The one or more computer processors aggregate the one or more alerts with additional data corresponding to the incident. The one or more computer processors feed the aggregated data into a prediction model, where training of the prediction model uses associated independent stacked Restricted Boltzmann Machines utilizing one or more supervised methods and one or more unsupervised methods. The one or more computer processors determine, based, at least in part, on one or more calculations by the prediction model, at least one probability of the incident. The one or more computer processors determine whether the at least one probability exceeds a pre-defined threshold. In response to determining the at least one probability exceeds a pre-defined threshold, the one or more computer processors send at least one notification.
    Type: Application
    Filed: September 29, 2015
    Publication date: March 30, 2017
    Inventors: Aaron K. Baughman, Christian Eggenberger, Andrea I. Martin, Daniel S. Stoessel, Craig M. Trim