Patents by Inventor Gideon Berger

Gideon Berger 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).

  • Method and system for data classification in the presence of a temporal non-stationarity
    Patent number: 8112417
    Abstract: A method and system for determining a feature of a particular pattern are provided. In particular, data records are received, and predetermined patterns that are associated with at least some of the data records are obtained. Using the system and method, particular information is extracted from at least a subset of the received data records, the particular information being indicative of the particular pattern in at least some of the data records. Then, it is determined whether the particular pattern is an unexpected pattern based on the obtained predetermined patterns. In addition, it is possible to classify and reduce data and/or parameters provided in the data records. First, the data records are received. Then, the data records which have at least one particular pattern are classified using a Multivariate Adaptive Regression Splines technique. Thereafter, the data and/or parameters of the classified data records are shrunk using a Stein's Estimator Rule technique.
    Type: Grant
    Filed: July 26, 2010
    Date of Patent: February 7, 2012
    Assignee: New York University
    Inventors: Gideon Berger, Bhubaneswar Mishra
  • Method and System for Data Classification in the Presence of a Temporal Non-Stationarity
    Publication number: 20100293124
    Abstract: A method and system for determining a feature of a particular pattern are provided. In particular, data records are received, and predetermined patterns that are associated with at least some of the data records are obtained. Using the system and method, particular information is extracted from at least a subset of the received data records, the particular information being indicative of the particular pattern in at least some of the data records. Then, it is determined whether the particular pattern is an unexpected pattern based on the obtained predetermined patterns. In addition, it is possible to classify and reduce data and/or parameters provided in the data records. First, the data records are received. Then, the data records which have at least one particular pattern are classified using a Multivariate Adaptive Regression Splines technique. Thereafter, the data and/or parameters of the classified data records are shrunk using a Stein's Estimator Rule technique.
    Type: Application
    Filed: July 26, 2010
    Publication date: November 18, 2010
    Applicant: New York University
    Inventors: Gideon Berger, Bhubaneswar Mishra
  • Method and system for data classification in the presence of a temporal non-stationarity
    Patent number: 7818318
    Abstract: A method and system for determining a feature of a particular pattern are provided. In particular, data records are received, and predetermined patterns that are associated with at least some of the data records are obtained. Using the system and method, particular information is extracted from at least a subset of the received data records, the particular information being indicative of the particular pattern in at least some of the data records. Then, it is determined whether the particular pattern is an unexpected pattern based on the obtained predetermined patterns. In addition, it is possible to classify and reduce data and/or parameters provided in the data records. First, the data records are received. Then, the data records which have at least one particular pattern are classified using a Multivariate Adaptive Regression Splines technique. Thereafter, the data and/or parameters of the classified data records are shrunk using a Stein's Estimator Rule technique.
    Type: Grant
    Filed: January 12, 2009
    Date of Patent: October 19, 2010
    Assignee: New York University
    Inventors: Gideon Berger, Bhubaneswar Mishra
  • METHOD AND SYSTEM FOR DATA CLASSIFICATION IN THE PRESENCE OF A TEMPORAL NON-STATIONARITY
    Publication number: 20090182701
    Abstract: A method and system for determining a feature of a particular pattern are provided. In particular, data records are received, and predetermined patterns that are associated with at least some of the data records are obtained. Using the system and method, particular information is extracted from at least a subset of the received data records, the particular information being indicative of the particular pattern in at least some of the data records. Then, it is determined whether the particular pattern is an unexpected pattern based on the obtained predetermined patterns. In addition, it is possible to classify and reduce data and/or parameters provided in the data records. First, the data records are received. Then, the data records which have at least one particular pattern are classified using a Multivariate Adaptive Regression Splines technique. Thereafter, the data and/or parameters of the classified data records are shrunk using a Stein's Estimator Rule technique.
    Type: Application
    Filed: January 12, 2009
    Publication date: July 16, 2009
    Applicant: New York University
    Inventors: Gideon Berger, Bhubaneswar Mishra
  • Method and system for data classification in the presence of a temporal non-stationarity
    Patent number: 7478077
    Abstract: A method and system for determining a feature of a particular pattern are provided. In particular, data records are received, and predetermined patterns that are associated with at least some of the data records are obtained. Using the system and method, particular information is extracted from at least a subset of the received data records, the particular information being indicative of the particular pattern in at least some of the data records. Then, it is determined whether the particular pattern is an unexpected pattern based on the obtained predetermined patterns. In addition, it is possible to classify and reduce data and/or parameters provided in the data records. First, the data records are received. Then, the data records which have at least one particular pattern are classified using a Multivariate Adaptive Regression Splines technique. Thereafter, the data and/or parameters of the classified data records are shrunk using a Stein's Estimator Rule technique.
    Type: Grant
    Filed: May 10, 2001
    Date of Patent: January 13, 2009
    Assignee: New York University
    Inventors: Gideon Berger, Bhubaneswar Mishra
  • Method and system for data classification in the presence of a temporal non-stationarity
    Publication number: 20040128267
    Abstract: A method and system for determining a feature of a particular pattern are provided. In particular, data records are received, and predetermined patterns that are associated with at least some of the data records are obtained. Using the system and method, particular information is extracted from at least a subset of the received data records, the particular information being indicative of the particular pattern in at least some of the data records. Then, it is determined whether the particular pattern is an unexpected pattern based on the obtained predetermined patterns. In addition, it is possible to classify and reduce data and/or parameters provided in the data records. First, the data records are received. Then, the data records which have at least one particular pattern are classified using a Multivariate Adaptive Regression Splines technique. Thereafter, the data and/or parameters of the classified data records are shrunk using a Stein's Estimator Rule technique.
    Type: Application
    Filed: April 22, 2003
    Publication date: July 1, 2004
    Inventors: Gideon Berger, Bhubaneswar Mishra