Patents by Inventor Dacheng XIU

Dacheng XIU 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).

  • Patent number: 11461847
    Abstract: Systems, methods, and computer-readable storage media facilitating automated testing of datasets including natural language data are disclosed. In the disclosed embodiments, rule sets may be used to condition and transform an input dataset into a format that is suitable for use with one or more artificial intelligence processes configured to extract parameters and classification information from the input dataset. The parameters and classes derived by the artificial intelligence processes may then be used to automatically generate various testing tools (e.g., scripts, test conditions, etc.) that may be executed against a test dataset, such as program code or other types of data.
    Type: Grant
    Filed: March 20, 2020
    Date of Patent: October 4, 2022
    Assignees: The University of Chicago, President and Fellows of Harvard College, Yale University
    Inventors: Dacheng Xiu, Zheng Tracy Ke, Bryan Kelly
  • Publication number: 20200302540
    Abstract: Systems, methods, and computer-readable storage media facilitating automated testing of datasets including natural language data are disclosed. In the disclosed embodiments, rule sets may be used to condition and transform an input dataset into a format that is suitable for use with one or more artificial intelligence processes configured to extract parameters and classification information from the input dataset. The parameters and classes derived by the artificial intelligence processes may then be used to automatically generate various testing tools (e.g., scripts, test conditions, etc.) that may be executed against a test dataset, such as program code or other types of data.
    Type: Application
    Filed: March 20, 2020
    Publication date: September 24, 2020
    Inventors: Dacheng Xiu, Zheng Tracy Ke, Bryan Kelly
  • Publication number: 20200273103
    Abstract: A security price volatility estimator that is capable of accurately estimating price volatility in real-time or near real-time, and in low noise and high noise environments. Embodiments cover an interactive tool that allows or instructs a user to make meaningful decisions based on the estimated volatility. The estimator is constructed based on the assumption that the transaction price of a security comprises the sum of (1) a latent efficient security price that follows a general Ito{circumflex over (?)} semimartingale, and (2) a market microstructure noise component that follows a discrete-time moving-average (MA)(?) process associated with the random execution of trades. The estimator is obtained by using a tractable Quasi-Maximum Likelihood Estimator (QMLE), which relies on a simple yet mis-specified moving-average MA(q+1) model for observed returns. The order of q is preferably selected based on Akaike Information Criteria (AIC) or Bayesian Information Criteria (BIC).
    Type: Application
    Filed: September 25, 2018
    Publication date: August 27, 2020
    Inventors: Dacheng XIU, Rui DA