Patents by Inventor Aman Dhesi
Aman Dhesi 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: 11961115Abstract: In some examples, a computing device may receive data from a plurality of groups of data sources. The computing device may access a plurality of data synthetization machine learning models configured for generating synthetic data. Respective ones of the data synthetization machine learning models may correspond to respective ones of the groups of data sources. The computing device generates first synthetic data by inputting, to a first data synthetization machine learning model, first data received from a first data source group, and generates second synthetic data by inputting, to a second data synthetization machine learning model, second data received from a second data source group. The computing device determines an allocation of resources based at least in part on comparing the first data and the first synthetic data with the second data and the second synthetic data.Type: GrantFiled: May 18, 2023Date of Patent: April 16, 2024Assignee: DOORDASH, INC.Inventors: Robert Bryant Kaspar, Alok Gupta, Aman Dhesi
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Publication number: 20230289847Abstract: In some examples, a computing device may receive data from a plurality of groups of data sources. The computing device may access a plurality of data synthetization machine learning models configured for generating synthetic data. Respective ones of the data synthetization machine learning models may correspond to respective ones of the groups of data sources. The computing device generates first synthetic data by inputting, to a first data synthetization machine learning model, first data received from a first data source group, and generates second synthetic data by inputting, to a second data synthetization machine learning model, second data received from a second data source group. The computing device determines an allocation of resources based at least in part on comparing the first data and the first synthetic data with the second data and the second synthetic data.Type: ApplicationFiled: May 18, 2023Publication date: September 14, 2023Inventors: Robert Bryant Kaspar, Alok Gupta, Aman Dhesi
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Patent number: 11682036Abstract: In some examples, a computing device may receive data from a plurality of groups of data sources. The computing device may create a training data set from a first portion of the received data and may create a plurality of validation data sets from a second portion of the received data. For example, each validation data set may correspond to a respective one of the groups of data sources. The computing device may train, using the training data set, a plurality of machine learning models configured for synthesizing data. For instance, respective ones of the machine learning models may correspond to respective ones of the groups of data sources. Further, the computing device may validate the respective machine learning models using the respective validation data set corresponding to the respective group to which the respective machine learning model being validated corresponds.Type: GrantFiled: March 10, 2021Date of Patent: June 20, 2023Assignee: DOORDASH, INC.Inventors: Robert Bryant Kaspar, Alok Gupta, Aman Dhesi
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Publication number: 20220292542Abstract: In some examples, a computing device may receive data from a plurality of groups of data sources. The computing device may create a training data set from a first portion of the received data and may create a plurality of validation data sets from a second portion of the received data. For example, each validation data set may correspond to a respective one of the groups of data sources. The computing device may train, using the training data set, a plurality of machine learning models configured for synthesizing data. For instance, respective ones of the machine learning models may correspond to respective ones of the groups of data sources. Further, the computing device may validate the respective machine learning models using the respective validation data set corresponding to the respective group to which the respective machine learning model being validated corresponds.Type: ApplicationFiled: March 10, 2021Publication date: September 15, 2022Inventors: Robert Bryant KASPAR, Alok GUPTA, Aman DHESI
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Publication number: 20210019694Abstract: The present disclosure generally pertains to systems and methods of order fulfillment using a fulfillment engine, which optimizes the allocation of client or user orders to third party merchants for fulfillment through the use of linear programming or machine learning. This optimization occurs by loading a series of relevant merchant attributes and client attributes into an optimizer with the order and analyzing the attributes to determine an optimal allocation of client orders to third party merchants. These orders are issued to the merchants and where necessary the system arranges delivery of the orders to the client. The system may also automatically update future orders in response to client feedback.Type: ApplicationFiled: July 13, 2020Publication date: January 21, 2021Applicant: DoorDash, Inc.Inventors: Aman Dhesi, Christopher Hollindale
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Patent number: 10671615Abstract: Exemplary embodiments relate to techniques for determining social networking or messaging user affinity and engagement coefficients (e.g., a measure of the connectedness between two people in a network). The described techniques are particularly well-suited to cases in which only limited information is available, such as when a new user joins a network and only the user's contacts list is available. The available information may be used to determine a group of existing users to which the new user is connected. Some embodiments relate to calculating scores among these existing users in order to infer an affinity for the new user to the existing users. Other embodiments involve calculating bilateral scores that reflect a degree of mutual affinity between two users.Type: GrantFiled: May 27, 2016Date of Patent: June 2, 2020Assignee: FACEBOOK, INC.Inventors: Ariel Benjamin Evnine, Zeev Rosenstein, Han Gyul Lee, Aman Dhesi
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Patent number: 10628427Abstract: Exemplary embodiments relate to techniques for determining social networking or messaging user affinity and engagement coefficients (e.g., a measure of the connectedness between two people in a network). The described techniques are particularly well-suited to cases in which only limited information is available, such as when a new user joins a network and only the user's contacts list is available. The available information may be used to determine a group of existing users to which the new user is connected. Some embodiments relate to calculating scores among these existing users in order to infer an affinity for the new user to the existing users. Other embodiments involve calculating bilateral scores that reflect a degree of mutual affinity between two users.Type: GrantFiled: May 27, 2016Date of Patent: April 21, 2020Assignee: FACEBOOK, INC.Inventors: Ariel Benjamin Evnine, Zeev Rosenstein, Han Gyul Lee, Aman Dhesi
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Patent number: 10601760Abstract: Techniques for device configuration of prospective contacts using messaging history information are described. In one embodiment, an apparatus may comprise a client front-end component operative to receive a client inbox request for a user account from a client device, the user account for a communication system; and send an ordered prospective contact list to the client device in response to the client inbox request; a prospective contact list component operative to generate a prospective contact list for a user account, wherein generating the prospective contact list for the user account excludes any existing contacts from an existing contact list for the user account; a predicted interest component operative to determine a predicted communication interest for each prospective contact on the prospective contact list; and a contact ranking component operative to determine a ranking weight for each prospective contact on the prospective contact list. Other embodiments are described and claimed.Type: GrantFiled: October 24, 2016Date of Patent: March 24, 2020Assignee: FACEBOOK, INC.Inventors: Han Gyul Lee, Louis Benoit Philippe Boval, Aman Dhesi
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Publication number: 20180113913Abstract: Techniques for device configuration of prospective contacts using messaging history information are described. In one embodiment, an apparatus may comprise a client front-end component operative to receive a client inbox request for a user account from a client device, the user account for a communication system; and send an ordered prospective contact list to the client device in response to the client inbox request; a prospective contact list component operative to generate a prospective contact list for a user account, wherein generating the prospective contact list for the user account excludes any existing contacts from an existing contact list for the user account; a predicted interest component operative to determine a predicted communication interest for each prospective contact on the prospective contact list; and a contact ranking component operative to determine a ranking weight for each prospective contact on the prospective contact list. Other embodiments are described and claimed.Type: ApplicationFiled: October 24, 2016Publication date: April 26, 2018Inventors: Han Gyul Lee, Louis Benoit Philippe Boval, Aman Dhesi
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Publication number: 20170344610Abstract: Exemplary embodiments relate to techniques for determining social networking or messaging user affinity and engagement coefficients (e.g., a measure of the connectedness between two people in a network). The described techniques are particularly well-suited to cases in which only limited information is available, such as when a new user joins a network and only the user's contacts list is available. The available information may be used to determine a group of existing users to which the new user is connected. Some embodiments relate to calculating scores among these existing users in order to infer an affinity for the new user to the existing users. Other embodiments involve calculating bilateral scores that reflect a degree of mutual affinity between two users.Type: ApplicationFiled: May 27, 2016Publication date: November 30, 2017Applicant: Facebook, Inc.Inventors: Ariel Benjamin Evnine, Zeev Rosenstein, Han Gyul Lee, Aman Dhesi
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Publication number: 20170344553Abstract: Exemplary embodiments relate to techniques for determining social networking or messaging user affinity and engagement coefficients (e.g., a measure of the connectedness between two people in a network). The described techniques are particularly well-suited to cases in which only limited information is available, such as when a new user joins a network and only the user's contacts list is available. The available information may be used to determine a group of existing users to which the new user is connected. Some embodiments relate to calculating scores among these existing users in order to infer an affinity for the new user to the existing users. Other embodiments involve calculating bilateral scores that reflect a degree of mutual affinity between two users.Type: ApplicationFiled: May 27, 2016Publication date: November 30, 2017Applicant: Facebook, Inc.Inventors: Ariel Benjamin Evnine, Zeev Rosenstein, Han Gyul Lee, Aman Dhesi