Patents by Inventor Aurelie Chloe LOZANO

Aurelie Chloe LOZANO 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).

  • Non-linear causal modeling from diverse data sources
    Patent number: 11860720
    Abstract: Techniques for causal modeling. Historical feature data is received, relating to a plurality of nodes in a system. A machine learning (ML) model is generated, for a node of the plurality of nodes. The ML model is trained to predict a plurality of future feature values for the node based on at least a portion of the historical feature data. A causal graph is generated, for the plurality of nodes, using a feature selection mechanism within the ML model. The feature selection mechanism includes a regularization term encouraging sparsity of nodes in selected features in the ML model.
    Type: Grant
    Filed: June 22, 2021
    Date of Patent: January 2, 2024
    Assignee: International Business Machines Corporation
    Inventors: Georgios Kollias, Aurelie Chloe Lozano, Naoki Abe
  • NON-LINEAR CAUSAL MODELING FROM DIVERSE DATA SOURCES
    Publication number: 20220405158
    Abstract: Techniques for causal modeling. Historical feature data is received, relating to a plurality of nodes in a system. A machine learning (ML) model is generated, for a node of the plurality of nodes. The ML model is trained to predict a plurality of future feature values for the node based on at least a portion of the historical feature data. A causal graph is generated, for the plurality of nodes, using a feature selection mechanism within the ML model. The feature selection mechanism includes a regularization term encouraging sparsity of nodes in selected features in the ML model.
    Type: Application
    Filed: June 22, 2021
    Publication date: December 22, 2022
    Inventors: Georgios KOLLIAS, Aurelie Chloe LOZANO, Naoki ABE