Patents by Inventor Michael A. Lazarus

Michael A. Lazarus 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: 20230151457
    Abstract: The invention relates to brass alloys that are substantially lead-free. In the alloys of the invention, lead is replaced with tellurium resulting in alloys that exhibit excellent machinability and conductivity.
    Type: Application
    Filed: January 2, 2023
    Publication date: May 18, 2023
    Applicant: AVIVA METALS, INC.
    Inventor: Norman Michael Lazarus
  • Patent number: 10967281
    Abstract: Disclosed are systems and methods for improving interactions with and between computers in content generating, searching, hosting and/or providing systems supported by or configured with personal computing devices, servers and/or platforms. The systems interact to identify and retrieve data within or across platforms, which can be used to improve the quality of data used in processing interactions between or among processors in such systems. The disclosed systems and methods provide systems and methods for automatic fantasy sports data analysis, including analysis of data to equalize player attractiveness in contestant composition of a fantasy sports team.
    Type: Grant
    Filed: November 3, 2019
    Date of Patent: April 6, 2021
    Assignee: VERIZON MEDIA INC.
    Inventors: Michael Lazarus, Maxim Sviridenko, Justin Thaler
  • Publication number: 20200286485
    Abstract: Methods and systems for transcribing a media file using a human intelligence task service and/or reinforcement learning are provided. The disclosed systems and methods provide opportunities for a segment of the input media file to be automatically re-analyzed, re-transcribed, and/or modified for re-transcription using a human intelligence task (HIT) service for verification and/or modification of the transcription results. The segment can also be reanalyzed, reconstructed, and re-transcribed using a reinforcement learning enabled transcription model.
    Type: Application
    Filed: September 24, 2019
    Publication date: September 10, 2020
    Inventors: Chad Steelberg, Wolf Kohn, Yanfang Shen, Cornelius Raths, Michael Lazarus, Peter Nguyen, Karl Schwamb
  • Publication number: 20200129867
    Abstract: Disclosed are systems and methods for improving interactions with and between computers in content generating, searching, hosting and/or providing systems supported by or configured with personal computing devices, servers and/or platforms. The systems interact to identify and retrieve data within or across platforms, which can be used to improve the quality of data used in processing interactions between or among processors in such systems. The disclosed systems and methods provide systems and methods for automatic fantasy sports data analysis, including analysis of data to equalize player attractiveness in contestant composition of a fantasy sports team.
    Type: Application
    Filed: November 3, 2019
    Publication date: April 30, 2020
    Inventors: Michael LAZARUS, Maxim SVIRIDENKO, Justin THALER
  • Publication number: 20190385610
    Abstract: Methods and systems for transcribing a media file using reinforcement learning are provided. In one aspect, the method includes: identifying a low confidence of accuracy portion from a transcription result of the media file; constructing a phoneme sequence that includes an audio segment corresponding to the identified low confidence of accuracy portion, based on at least on a reward function; creating a new audio waveform based at least on the constructed phoneme sequence; and generating a new transcription using a transcription engine based on the new audio waveform.
    Type: Application
    Filed: December 10, 2018
    Publication date: December 19, 2019
    Inventors: Chad Steelberg, Wolf Kohn, Yanfang Shen, Cornelius Raths, Michael Lazarus, Peter Nguyen
  • Patent number: 10463975
    Abstract: Disclosed are systems and methods for improving interactions with and between computers in content generating, searching, hosting and/or providing systems supported by or configured with personal computing devices, servers and/or platforms. The systems interact to identify and retrieve data within or across platforms, which can be used to improve the quality of data used in processing interactions between or among processors in such systems. The disclosed systems and methods provide systems and methods for automatic fantasy sports data analysis, including analysis of data to equalize player attractiveness in contestant composition of a fantasy sports team.
    Type: Grant
    Filed: June 30, 2016
    Date of Patent: November 5, 2019
    Assignee: OATH INC.
    Inventors: Michael Lazarus, Maxim Sviridenko, Justin Thaler
  • Publication number: 20180001215
    Abstract: Disclosed are systems and methods for improving interactions with and between computers in content generating, searching, hosting and/or providing systems supported by or configured with personal computing devices, servers and/or platforms. The systems interact to identify and retrieve data within or across platforms, which can be used to improve the quality of data used in processing interactions between or among processors in such systems. The disclosed systems and methods provide systems and methods for automatic fantasy sports data analysis, including analysis of data to equalize player attractiveness in contestant composition of a fantasy sports team.
    Type: Application
    Filed: June 30, 2016
    Publication date: January 4, 2018
    Inventors: Michael Lazarus, Maxim Sviridenko, Justin Thaler
  • Publication number: 20170145544
    Abstract: The invention relates to brass alloys that are substantially lead-free. In the alloys of the invention, lead is replaced with tellurium resulting in alloys that exhibit excellent machinability and conductivity.
    Type: Application
    Filed: October 10, 2016
    Publication date: May 25, 2017
    Inventor: Norman Michael Lazarus
  • Patent number: 9311611
    Abstract: A method for service level management comprises identifying connected enterprise application components and, under control of an automated system, relating historical performance for the connected enterprise application components and electronically creating a service level agreement based on the historical performance relation.
    Type: Grant
    Filed: June 16, 2006
    Date of Patent: April 12, 2016
    Assignee: Hewlett Packard Enterprise Development LP
    Inventors: Myles Suer, Barbara Newton, David Baron, Michael Lazarus
  • Patent number: 8296250
    Abstract: A system and method for protecting identity fraud are disclosed. A system includes a detection subsystem to identify applications and/or accounts at risk of identity fraud, and a disposition subsystem to process data provided by the detection system and to determine whether identity fraud exists in the applications and/or accounts. According to an implementation, one or more neural network models are defined, each neural network model being configured to handle a class of cases related to the subject and a specific data configuration describing a case of the class. The one or more neural network models are run to generate data requests about the subject's identity, and the data requests are passed to a detection system that monitor transactions associated with the subject. Additional data associated with the transactions is requested until a threshold certainty is achieved or until available data or models are exhausted.
    Type: Grant
    Filed: August 1, 2011
    Date of Patent: October 23, 2012
    Assignee: Fair Isaac Corporation
    Inventors: Theodore J. Crooks, Uwe F. Mayer, Michael A. Lazarus
  • Publication number: 20110289032
    Abstract: A system and method for protecting identity fraud are disclosed. A system includes a detection subsystem to identify applications and/or accounts at risk of identity fraud, and a disposition subsystem to process data provided by the detection system and to determine whether identity fraud exists in the applications and/or accounts. According to an implementation, one or more neural network models are defined, each neural network model being configured to handle a class of cases related to the subject and a specific data configuration describing a case of the class. The one or more neural network models are run to generate data requests about the subject's identity, and the data requests are passed to a detection system that monitor transactions associated with the subject. Additional data associated with the transactions is requested until a threshold certainty is achieved or until available data or models are exhausted.
    Type: Application
    Filed: August 1, 2011
    Publication date: November 24, 2011
    Inventors: Theodore J. Crooks, Uwe F. Mayer, Michael A. Lazarus
  • Patent number: 7991716
    Abstract: A system and method for protecting identity fraud are disclosed. A system includes a detection subsystem to identify applications and/or accounts at risk of identity fraud, and a disposition subsystem to process data provided by the detection system and to determine whether identity fraud exists in the applications and/or accounts. According to an implementation, one or more neural network models are defined, each neural network model being configured to handle a class of cases related to the subject and a specific data configuration describing a case of the class. The one or more neural network models are run to generate data requests about the subject's identity, and the data requests are passed to a detection system that monitor transactions associated with the subject. Additional data associated with the transactions is requested until a threshold certainty is achieved or until available data or models are exhausted.
    Type: Grant
    Filed: December 6, 2010
    Date of Patent: August 2, 2011
    Assignee: Fair Isaac Corporation
    Inventors: Theodore J. Crooks, Uwe F. Mayer, Michael A. Lazarus
  • Publication number: 20110137840
    Abstract: A system and method for protecting identity fraud are disclosed. A system includes a detection subsystem to identify applications and/or accounts at risk of identity fraud, and a disposition subsystem to process data provided by the detection system and to determine whether identity fraud exists in the applications and/or accounts. According to an implementation, one or more neural network models are defined, each neural network model being configured to handle a class of cases related to the subject and a specific data configuration describing a case of the class. The one or more neural network models are run to generate data requests about the subject's identity, and the data requests are passed to a detection system that monitor transactions associated with the subject. Additional data associated with the transactions is requested until a threshold certainty is achieved or until available data or models are exhausted.
    Type: Application
    Filed: December 6, 2010
    Publication date: June 9, 2011
    Inventors: Theodore J. Crooks, Uwe F. Mayer, Michael A. Lazarus
  • Patent number: 7849029
    Abstract: A system and method for protecting identity fraud are disclosed. A system includes a detection subsystem to identify applications and/or accounts at risk of identity fraud, and a disposition subsystem to process data provided by the detection system and to determine whether identity fraud exists in the applications and/or accounts. According to an implementation, one or more neural network models are defined, each neural network model being configured to handle a class of cases related to the subject and a specific data configuration describing a case of the class. The one or more neural network models are run to generate data requests about the subject's identity, and the data requests are passed to a detection system that monitor transactions associated with the subject. Additional data associated with the transactions is requested until a threshold certainty is achieved or until available data or models are exhausted.
    Type: Grant
    Filed: June 2, 2006
    Date of Patent: December 7, 2010
    Assignee: Fair Isaac Corporation
    Inventors: Theodore J. Crooks, Uwe F. Mayer, Michael A. Lazarus
  • Patent number: 7533038
    Abstract: Predictive modeling of consumer financial behavior, including determination of likely responses to particular marketing efforts, is provided by application of consumer transaction data to predictive models associated with merchant segments. The merchant segments are derived from the consumer transaction data based on co-occurrences of merchants in sequences of transactions. Merchant vectors represent specific merchants, and are aligned in a vector space as a function of the degree to which the merchants co-occur more or less frequently than expected. Supervised segmentation is applied to merchant vectors to form the merchant segments. Merchant segment predictive models provide predictions of spending in each merchant segment for any particular consumer, based on previous spending by the consumer. Consumer profiles describe summary statistics of each consumer's spending in the merchant segments, and across merchant segments.
    Type: Grant
    Filed: January 15, 2007
    Date of Patent: May 12, 2009
    Assignee: Fair Isaac Corporation
    Inventors: Matthias Blume, Michael A. Lazarus, Larry S. Peranich, Frederique Vernhes, Kenneth B. Brown, William R. Caid, Ted E. Dunning, Gerald R. Russell, Kevin L. Sitze
  • Publication number: 20070294406
    Abstract: A method for service level management comprises identifying connected enterprise application components and, under control of an automated system, relating historical performance for the connected enterprise application components and electronically creating a service level agreement based on the historical performance relation.
    Type: Application
    Filed: June 16, 2006
    Publication date: December 20, 2007
    Inventors: Myles Suer, Barbara Newton, David Baron, Michael Lazarus
  • Publication number: 20070244741
    Abstract: Predictive modeling of consumer financial behavior, including determination of likely responses to particular marketing efforts, is provided by application of consumer transaction data to predictive models associated with merchant segments. The merchant segments are derived from the consumer transaction data based on co-occurrences of merchants in sequences of transactions. Merchant vectors represent specific merchants, and are aligned in a vector space as a function of the degree to which the merchants co-occur more or less frequently than expected. Supervised segmentation is applied to merchant vectors to form the merchant segments. Merchant segment predictive models provide predictions of spending in each merchant segment for any particular consumer, based on previous spending by the consumer. Consumer profiles describe summary statistics of each consumer's spending in the merchant segments, and across merchant segments.
    Type: Application
    Filed: January 15, 2007
    Publication date: October 18, 2007
    Inventors: Matthias Blume, Michael Lazarus, Larry Peranich, Frederique Vernhes, Kenneth Brown, William Caid, Ted Dunning, Gerald Russell, Kevin Sitze
  • Publication number: 20070124256
    Abstract: A system and method for protecting identity fraud are disclosed. A system includes a detection subsystem to identify applications and/or accounts at risk of identity fraud, and a disposition subsystem to process data provided by the detection system and to determine whether identity fraud exists in the applications and/or accounts. According to an implementation, one or more neural network models are defined, each neural network model being configured to handle a class of cases related to the subject and a specific data configuration describing a case of the class. The one or more neural network models are run to generate data requests about the subject's identity, and the data requests are passed to a detection system that monitor transactions associated with the subject. Additional data associated with the transactions is requested until a threshold certainty is achieved or until available data or models are exhausted.
    Type: Application
    Filed: June 2, 2006
    Publication date: May 31, 2007
    Inventors: Theodore Crooks, Uwe Mayer, Michael Lazarus
  • Patent number: RE42577
    Abstract: Predictive modeling of consumer financial behavior, including determination of likely responses to particular marketing efforts, is provided by application of consumer transaction data to predictive models associated with merchant segments. The merchant segments are derived from the consumer transaction data based on co-occurrences of merchants in sequences of transactions. Merchant vectors represent specific merchants, and are aligned in a vector space as a function of the degree to which the merchants co-occur more or less frequently than expected. Supervised segmentation is applied to merchant vectors to form the merchant segments. Merchant segment predictive models provide predictions of spending in each merchant segment for any particular consumer, based on previous spending by the consumer. Consumer profiles describe summary statistics of each consumer's spending in the merchant segments, and across merchant segments.
    Type: Grant
    Filed: March 22, 2010
    Date of Patent: July 26, 2011
    Assignee: Kuhuro Investments AG, L.L.C.
    Inventors: Matthias Blume, Michael A. Lazarus, Larry S. Peranich, Frederique Vernhes, William R. Caid, Ted E. Dunning, Gerald S. Russell, Kevin L. Sitze
  • Patent number: RE42663
    Abstract: Predictive modeling of consumer financial behavior, including determination of likely responses to particular marketing efforts, is provided by application of consumer transaction data to predictive models associated with merchant segments, which are derived from the consumer transaction data based on co-occurrences of merchants in sequences of transactions. Merchant vectors represent specific merchants, and are aligned in a vector space as a function of the degree to which the merchants co-occur. Supervised segmentation is applied to merchant vectors to form merchant segments. Merchant segment predictive models provide predictions of spending in each merchant segment for any particular consumer, based on previous spending by the consumer. Consumer profiles describe summary statistics of each consumer's spending in the merchant segments, and across merchant segments. Consumer profiles include consumer vectors derived as summary vectors of selected merchants patronized by the consumer.
    Type: Grant
    Filed: March 22, 2010
    Date of Patent: August 30, 2011
    Assignee: Kuhuro Investments AG, L.L.C.
    Inventors: Michael Lazarus, Larry S. Peranich, Frederique Vernhes, A. U. Matthias Blume, William R. Caid, Ted E. Dunning, Gerald R. Russell, Kevin Sitze