Patents by Inventor David DiCato
David DiCato 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).
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Patent number: 11429915Abstract: Systems and methods for predicting feature values in a matrix are disclosed. In example embodiments, a server accesses a matrix, the matrix having multiple dimensions, one dimension of the matrix representing features, and one dimension of the matrix representing entities. The server separates the matrix into multiple submatrices along a first dimension, each submatrix including all cells in the matrix for a set of values in the first dimension. The server provides the multiple submatrices to multiple machines. The server computes, using each machine, a correlation between values in at least one second dimension of the matrix and a value for a preselected feature in the matrix, the correlation being used to predict the value for the preselected feature based on other values along the at least one second dimension. The server provides an output representing the computed correlation.Type: GrantFiled: November 30, 2017Date of Patent: August 30, 2022Assignee: Microsoft Technology Licensing, LLCInventors: Gio Borje, Benjamin John McCann, David DiCato, Jerry Lin, Skylar Payne, Apoorv Khandelwal, Nadeem Anjum
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Patent number: 11010688Abstract: Systems and methods for predicting feature values in a matrix are disclosed. In example embodiments, a server accesses a matrix, the matrix having multiple dimensions, one dimension of the matrix representing features, and one dimension of the matrix representing entities. The server separates the matrix into multiple submatrices along a first dimension, each submatrix including all cells in the matrix for a set of values in the first dimension. The server provides the multiple submatrices to multiple machines. The server computes, using each machine, a correlation between values in at least one second dimension of the matrix and a value for a preselected feature in the matrix, the correlation being used to predict the value for the preselected feature based on other values along the at least one second dimension. The server provides an output representing the computed correlation.Type: GrantFiled: November 30, 2017Date of Patent: May 18, 2021Assignee: Microsoft Technology Licensing, LLCInventors: Gio Borje, Benjamin John McCann, David DiCato, Jerry Lin, Skylar Payne, Apoorv Khandelwal, Nadeem Anjum
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Patent number: 10679188Abstract: Systems and methods for predicting feature values in a matrix are disclosed. In example embodiments, a server accesses a matrix, the matrix having multiple dimensions, one dimension of the matrix representing features, and one dimension of the matrix representing entities. The server separates the matrix into multiple submatrices along a first dimension, each submatrix including all cells in the matrix for a set of values in the first dimension. The server provides the multiple submatrices to multiple machines. The server computes, using each machine, a correlation between values in at least one second dimension of the matrix and a value for a preselected feature in the matrix, the correlation being used to predict the value for the preselected feature based on other values along the at least one second dimension. The server provides an output representing the computed correlation.Type: GrantFiled: November 30, 2017Date of Patent: June 9, 2020Assignee: Microsoft Technology Licensing, LLCInventors: Gio Borje, Benjamin John McCann, David DiCato, Jerry Lin, Skylar Payne, Apoorv Khandelwal, Nadeem Anjum
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Patent number: 10521489Abstract: Systems and methods for predicting feature values in a matrix are disclosed. In example embodiments, a server accesses a matrix, the matrix having multiple dimensions, one dimension of the matrix representing features, and one dimension of the matrix representing entities. The server separates the matrix into multiple submatrices along a first dimension, each submatrix including all cells in the matrix for a set of values in the first dimension. The server provides the multiple submatrices to multiple machines. The server computes, using each machine, a correlation between values in at least one second dimension of the matrix and a value for a preselected feature in the matrix, the correlation being used to predict the value for the preselected feature based on other values along the at least one second dimension. The server provides an output representing the computed correlation.Type: GrantFiled: November 30, 2017Date of Patent: December 31, 2019Assignee: Microsoft Technology Licensing, LLCInventors: Gio Borje, Benjamin John McCann, David DiCato, Jerry Lin, Skylar Payne, Apoorv Khandelwal, Nadeem Anjum
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Publication number: 20190287070Abstract: Systems and methods for query expansion are disclosed. In some examples, a server receives, from a client device, a search query for employment candidates, the search query comprising a first set of parameters. The server determines a second set of parameters related to the first set of parameters in response to identifying a second parameter for the second set of parameters that corresponds with a first parameter from the first set of parameters, the professional records being stored in a professional data repository. The server generates, from the professional data repository, a first set of search results based on the first set of parameters and the second set of parameters. The server provides, to the client device, an output representing the first set of search results.Type: ApplicationFiled: March 15, 2018Publication date: September 19, 2019Inventors: Erik Eugene Buchanan, Vijay Dialani, Sahin Cem Geyik, Benjamin John McCann, Ketan Thakkar, Patrick Cheung, Nadeem Anjum, David DiCato
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Publication number: 20190163668Abstract: Systems and methods for predicting feature values in a matrix are disclosed. In example embodiments, a server accesses a matrix, the matrix having multiple dimensions, one dimension of the matrix representing features, and one dimension of the matrix representing entities. The server separates the matrix into multiple submatrices along a first dimension, each submatrix including all cells in the matrix for a set of values in the first dimension. The server provides the multiple submatrices to multiple machines. The server computes, using each machine, a correlation between values in at least one second dimension of the matrix and a value for a preselected feature in the matrix, the correlation being used to predict the value for the preselected feature based on other values along the at least one second dimension. The server provides an output representing the computed correlation.Type: ApplicationFiled: November 30, 2017Publication date: May 30, 2019Inventors: Gio Borje, Benjamin John McCann, David DiCato, Jerry Lin, Skylar Payne, Apoorv Khandelwal, Nadeem Anjum
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Publication number: 20190163718Abstract: Systems and methods for predicting feature values in a matrix are disclosed. In example embodiments, a server accesses a matrix, the matrix having multiple dimensions, one dimension of the matrix representing features, and one dimension of the matrix representing entities. The server separates the matrix into multiple submatrices along a first dimension, each submatrix including all cells in the matrix for a set of values in the first dimension. The server provides the multiple submatrices to multiple machines. The server computes, using each machine, a correlation between values in at least one second dimension of the matrix and a value for a preselected feature in the matrix, the correlation being used to predict the value for the preselected feature based on other values along the at least one second dimension. The server provides an output representing the computed correlation.Type: ApplicationFiled: November 30, 2017Publication date: May 30, 2019Inventors: Gio Borje, Benjamin John McCann, David DiCato, Jerry Lin, Skylar Payne, Apoorv Khandelwal, Nadeem Anjum
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Publication number: 20190164096Abstract: Systems and methods for predicting feature values in a matrix are disclosed. In example embodiments, a server accesses a matrix, the matrix having multiple dimensions, one dimension of the matrix representing features, and one dimension of the matrix representing entities. The server separates the matrix into multiple submatrices along a first dimension, each submatrix including all cells in the matrix for a set of values in the first dimension. The server provides the multiple submatrices to multiple machines. The server computes, using each machine, a correlation between values in at least one second dimension of the matrix and a value for a preselected feature in the matrix, the correlation being used to predict the value for the preselected feature based on other values along the at least one second dimension. The server provides an output representing the computed correlation.Type: ApplicationFiled: November 30, 2017Publication date: May 30, 2019Inventors: Gio Borje, Benjamin John McCann, David DiCato, Jerry Lin, Skylar Payne, Apoorv Khandelwal, Nadeem Anjum
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Publication number: 20190164132Abstract: Systems and methods for predicting feature values in a matrix are disclosed. In example embodiments, a server accesses a matrix, the matrix having multiple dimensions, one dimension of the matrix representing features, and one dimension of the matrix representing entities. The server separates the matrix into multiple submatrices along a first dimension, each submatrix including all cells in the matrix for a set of values in the first dimension. The server provides the multiple submatrices to multiple machines. The server computes, using each machine, a correlation between values in at least one second dimension of the matrix and a value for a preselected feature in the matrix, the correlation being used to predict the value for the preselected feature based on other values along the at least one second dimension. The server provides an output representing the computed correlation.Type: ApplicationFiled: November 30, 2017Publication date: May 30, 2019Inventors: Gio Borje, Benjamin John McCann, David DiCato, Jerry Lin, Skylar Payne, Apoorv Khandelwal, Nadeem Anjum