Patents by Inventor Ryan Hsu
Ryan Hsu 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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Publication number: 20240134052Abstract: Systems and techniques of the present disclosure may access data from a time-of-flight (TOF) sensor of an autonomous vehicle (AV). The TOF sensor may have light signals and received reflections of those transmitted signals such that a set of simulation data can be generated. This set of simulation data may identify a distance to associate with an object that is different from a calibration distance. Equations may be used to identify a light signal amplitude, a signal to noise ratio (SNR), and a range inaccuracy due to noise from the accessed data. The identified the light signal amplitude, the SNR, and the range inaccuracy due to noise may have been identified using equations. Once the set of simulation data is generated, it may be saved for later access by a processor executing a simulation program used to train devices used to control the driving of an AV.Type: ApplicationFiled: October 23, 2022Publication date: April 25, 2024Inventors: Brett Berger, Ryan Suess, Amin Aghaei, Stephanie Hsu
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Patent number: 11868856Abstract: A method comprises receiving a network of a plurality of nodes and a plurality of edges, each of the nodes of the plurality of nodes comprising members representative of at least one subset of initial data points, selecting a subset of the data points based on each node of the plurality of nodes, for each selected data point of the set of selected data points, determining a predetermined number of other data points that are closest in distance to that particular selected data point, grouping the selected data points into a plurality of groups based, at least in part, on the predetermined number of other data points of the set of selected data points that are closest in distance, each group of the plurality of groups including a different subset of data points, and providing a list of selected data points and the plurality of groups.Type: GrantFiled: February 4, 2022Date of Patent: January 9, 2024Assignee: SymphonyAI Sensa LLCInventors: Ajithkumar Warrier, Jennifer Kloke, Ryan Hsu, Sudhakar Jonnalagadda
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Publication number: 20220391415Abstract: An example method comprises receiving data points, determining at least one size of a plurality of subsets based on a constraint of at least one computation device or an analysis server, transferring each of the subsets to different computation devices, each computation device selecting a group of data points to generate a first sub-subset of landmarks, add non-landmark data points that have the farthest distance to the closest landmark to create an expanded sub-subset of landmarks, create an analysis landmark set based on a combination of expanded sub-subsets of expanded landmarks from different computation devices, perform a similarity function on the analysis landmark set, generate a cover of the mathematical reference space to create overlapping subsets, cluster the mapped landmark points based on the overlapping subsets, create a plurality of nodes, each node being based on the clustering, each landmark point being a member of at least one node.Type: ApplicationFiled: July 22, 2022Publication date: December 8, 2022Applicant: Ayasdi AI LLCInventors: Gurjeet Singh, Lawrence Spracklen, Ryan Hsu
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Patent number: 11397753Abstract: An example method comprises receiving data points, determining at least one size of a plurality of subsets based on a constraint of at least one computation device or an analysis server, transferring each of the subsets to different computation devices, each computation device selecting a group of data points to generate a first sub-subset of landmarks, add non-landmark data points that have the farthest distance to the closest landmark to create an expanded sub-subset of landmarks, create an analysis landmark set based on a combination of expanded sub-subsets of expanded landmarks from different computation devices, perform a similarity function on the analysis landmark set, generate a cover of the mathematical reference space to create overlapping subsets, cluster the mapped landmark points based on the overlapping subsets, create a plurality of nodes, each node being based on the clustering, each landmark point being a member of at least one node.Type: GrantFiled: February 26, 2019Date of Patent: July 26, 2022Assignee: Ayasdi AI LLCInventors: Gurjeet Singh, Lawrence Spracklen, Ryan Hsu
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Publication number: 20220199263Abstract: A method comprises receiving a network of a plurality of nodes and a plurality of edges, each of the nodes of the plurality of nodes comprising members representative of at least one subset of initial data points, selecting a subset of the data points based on each node of the plurality of nodes, for each selected data point of the set of selected data points, determining a predetermined number of other data points that are closest in distance to that particular selected data point, grouping the selected data points into a plurality of groups based, at least in part, on the predetermined number of other data points of the set of selected data points that are closest in distance, each group of the plurality of groups including a different subset of data points, and providing a list of selected data points and the plurality of groups.Type: ApplicationFiled: February 4, 2022Publication date: June 23, 2022Applicant: Ayasdi AI LLCInventors: Ajithkumar Warrier, Jennifer Kloke, Ryan Hsu, Sudhakar Jonnalagadda
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Patent number: 11244765Abstract: A method comprises receiving a network of a plurality of nodes and a plurality of edges, each of the nodes of the plurality of nodes comprising members representative of at least one subset of initial data points, selecting a subset of the data points based on each node of the plurality of nodes, for each selected data point of the set of selected data points, determining a predetermined number of other data points that are closest in distance to that particular selected data point, grouping the selected data points into a plurality of groups based, at least in part, on the predetermined number of other data points of the set of selected data points that are closest in distance, each group of the plurality of groups including a different subset of data points, and providing a list of selected data points and the plurality of groups.Type: GrantFiled: June 28, 2018Date of Patent: February 8, 2022Assignee: Ayasdi AI LLCInventors: Ajithkumar Warrier, Jennifer Kloke, Ryan Hsu, Sudhakar Jonnalagadda
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Publication number: 20200042539Abstract: An example method comprises receiving data points, determining at least one size of a plurality of subsets based on a constraint of at least one computation device or an analysis server, transferring each of the subsets to different computation devices, each computation device selecting a group of data points to generate a first sub-subset of landmarks, add non-landmark data points that have the farthest distance to the closest landmark to create an expanded sub-subset of landmarks, create an analysis landmark set based on a combination of expanded sub-subsets of expanded landmarks from different computation devices, perform a similarity function on the analysis landmark set, generate a cover of the mathematical reference space to create overlapping subsets, cluster the mapped landmark points based on the overlapping subsets, create a plurality of nodes, each node being based on the clustering, each landmark point being a member of at least one node.Type: ApplicationFiled: February 26, 2019Publication date: February 6, 2020Applicant: Ayasdi, Inc.Inventors: Gurjeet Singh, Lawrence Spracklen, Ryan Hsu
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Patent number: 10216828Abstract: An example method comprises receiving data points, determining at least one size of a plurality of subsets based on a constraint of at least one computation device or an analysis server, transferring each of the subsets to different computation devices, each computation device selecting a group of data points to generate a first sub-subset of landmarks, add non-landmark data points that have the farthest distance to the closest landmark to create an expanded sub-subset of landmarks, create an analysis landmark set based on a combination of expanded sub-subsets of expanded landmarks from different computation devices, perform a similarity function on the analysis landmark set, generate a cover of the mathematical reference space to create overlapping subsets, cluster the mapped landmark points based on the overlapping subsets, create a plurality of nodes, each node being based on the clustering, each landmark point being a member of at least one node.Type: GrantFiled: May 5, 2016Date of Patent: February 26, 2019Assignee: Ayasdi, Inc.Inventors: Gurjeet Singh, Lawrence Spracklen, Ryan Hsu
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Publication number: 20190005115Abstract: A method comprises receiving a network of a plurality of nodes and a plurality of edges, each of the nodes of the plurality of nodes comprising members representative of at least one subset of initial data points, selecting a subset of the data points based on each node of the plurality of nodes, for each selected data point of the set of selected data points, determining a predetermined number of other data points that are closest in distance to that particular selected data point, grouping the selected data points into a plurality of groups based, at least in part, on the predetermined number of other data points of the set of selected data points that are closest in distance, each group of the plurality of groups including a different subset of data points, and providing a list of selected data points and the plurality of groups.Type: ApplicationFiled: June 28, 2018Publication date: January 3, 2019Applicant: Ayasdi, Inc.Inventors: Ajithkumar Warrier, Jennifer Kloke, Ryan Hsu, Sudhakar Jonnalagadda
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Publication number: 20180025073Abstract: A method comprises dividing a set of data points into a structure subset and boost subsets, adding the data points in structure subset into each boost subset, analyzing the structure subset using topological data analysis (TDA) to identify nodes of a structure graph, boost graph, and modified graph, analyze each of the boost subsets using the TDA to identify additional nodes of boost graph, for each node in each of the plurality of boost graphs that do not share at least one data point with a node in the structure graph, adding the node of a particular boost subset including data points that are members of the node, to the modified graph, and generating report indicating relationships between data points of the set of data points based on the nodes of the modified graph.Type: ApplicationFiled: July 21, 2017Publication date: January 25, 2018Applicant: Ayasdi, Inc.Inventors: Gurjeet Singh, Ryan Hsu, Gunnar Carlsson
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Publication number: 20160246871Abstract: An example method comprises receiving data points, determining at least one size of a plurality of subsets based on a constraint of at least one computation device or an analysis server, transferring each of the subsets to different computation devices, each computation device selecting a group of data points to generate a first sub-subset of landmarks, add non-landmark data points that have the farthest distance to the closest landmark to create an expanded sub-subset of landmarks, create an analysis landmark set based on a combination of expanded sub-subsets of expanded landmarks from different computation devices, perform a similarity function on the analysis landmark set, generate a cover of the mathematical reference space to create overlapping subsets, cluster the mapped landmark points based on the overlapping subsets, create a plurality of nodes, each node being based on the clustering, each landmark point being a member of at least one node.Type: ApplicationFiled: May 5, 2016Publication date: August 25, 2016Inventors: Gurjeet Singh, Lawrence Spracklen, Ryan Hsu
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Publication number: 20080007635Abstract: The system according to the present invention includes a light-diffusing screen having a projected image that includes the intrinsic random optical patterns superimposed on a scene image. An electronic photosensor is used to capturing the scene image and an image processor employs algorithms that reduce the random optical patterns that are inherent to the light-diffusing screen.Type: ApplicationFiled: December 30, 2005Publication date: January 10, 2008Inventors: Ryan Hsu, James Stoops