Patents by Inventor Vladan Radosavljevic
Vladan Radosavljevic 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: 11835951Abstract: Systems and methods for predicting object motion and controlling autonomous vehicles are provided. In one example embodiment, a computer implemented method includes obtaining state data indicative of at least a current or a past state of an object that is within a surrounding environment of an autonomous vehicle. The method includes obtaining data associated with a geographic area in which the object is located. The method includes generating a combined data set associated with the object based at least in part on a fusion of the state data and the data associated with the geographic area in which the object is located. The method includes obtaining data indicative of a machine-learned model. The method includes inputting the combined data set into the machine-learned model. The method includes receiving an output from the machine-learned model. The output can be indicative of a plurality of predicted trajectories of the object.Type: GrantFiled: September 3, 2021Date of Patent: December 5, 2023Assignee: UATC, LLCInventors: Nemanja Djuric, Vladan Radosavljevic, Thi Duong Nguyen, Tsung-Han Lin, Jeff Schneider, Henggang Cui, Fang-Chieh Chou, Tzu-Kuo Huang
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Patent number: 11488277Abstract: A transport system can manage an on-demand transportation service to connect available vehicles with users, and can compile ride history data for each user. The ride history data can indicate the contextual usage of the on-demand transportation service by the user. Based on the ride history data, the transport system can determine demographic and personal interest information of the respective user. The transport system may then personalize one or more ride characteristics of any ride requested by the user based on the demographic and personal interest information determined from the ride history of the user.Type: GrantFiled: November 8, 2019Date of Patent: November 1, 2022Assignee: Uber Technologies, Inc.Inventors: Nemanja Djuric, Vladan Radosavljevic
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Patent number: 11263664Abstract: Disclosed are systems and methods for improving interactions with and between computers in content searching, generating, 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 transform user search keywords into equivalent keyword formats commonly used and/or found within messaging platforms, and compile a data set from such information from which a search for content can be based. The present disclosure, therefore, provides systems and methods that augment users' search terms with terms found in users' mailboxes for purposes of searching for, identifying and communicating content that is relevant to those users.Type: GrantFiled: December 30, 2015Date of Patent: March 1, 2022Assignee: YAHOO ASSETS LLCInventors: Varun Bhagwan, Blake Carpenter, Mihajlo Grbovic, Doug Sharp, Vladan Radosavljevic, Nemanja Djuric
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Publication number: 20210397185Abstract: Systems and methods for predicting object motion and controlling autonomous vehicles are provided. In one example embodiment, a computer implemented method includes obtaining state data indicative of at least a current or a past state of an object that is within a surrounding environment of an autonomous vehicle. The method includes obtaining data associated with a geographic area in which the object is located. The method includes generating a combined data set associated with the object based at least in part on a fusion of the state data and the data associated with the geographic area in which the object is located. The method includes obtaining data indicative of a machine-learned model. The method includes inputting the combined data set into the machine-learned model. The method includes receiving an output from the machine-learned model. The output can be indicative of a plurality of predicted trajectories of the object.Type: ApplicationFiled: September 3, 2021Publication date: December 23, 2021Inventors: Nemanja Djuric, Vladan Radosavljevic, Thi Duong Nguyen, Tsung-Han Lin, Jeff Schneider, Henggang Cui, Fang-Chieh Chou, Tzu-Kuo Huang
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Patent number: 11112796Abstract: Systems and methods for predicting object motion and controlling autonomous vehicles are provided. In one example embodiment, a computer implemented method includes obtaining state data indicative of at least a current or a past state of an object that is within a surrounding environment of an autonomous vehicle. The method includes obtaining data associated with a geographic area in which the object is located. The method includes generating a combined data set associated with the object based at least in part on a fusion of the state data and the data associated with the geographic area in which the object is located. The method includes obtaining data indicative of a machine-learned model. The method includes inputting the combined data set into the machine-learned model. The method includes receiving an output from the machine-learned model. The output can be indicative of a plurality of predicted trajectories of the object.Type: GrantFiled: September 5, 2018Date of Patent: September 7, 2021Assignee: UATC, LLCInventors: Nemanja Djuric, Vladan Radosavljevic, Thi Duong Nguyen, Tsung-Han Lin, Jeff Schneider, Henggang Cui, Fang-Chieh Chou, Tzu-Kuo Huang
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Patent number: 10656657Abstract: Systems and methods for predicting object motion and controlling autonomous vehicles are provided. In one example embodiment, a computer implemented method includes obtaining state data indicative of at least a current or a past state of an object that is within a surrounding environment of an autonomous vehicle. The method includes obtaining data associated with a geographic area in which the object is located. The method includes generating a combined data set associated with the object based at least in part on a fusion of the state data and the data associated with the geographic area in which the object is located. The method includes obtaining data indicative of a machine-learned model. The method includes inputting the combined data set into the machine-learned model. The method includes receiving an output from the machine-learned model. The output can be indicative of a predicted trajectory of the object.Type: GrantFiled: October 13, 2017Date of Patent: May 19, 2020Assignee: UATC, LLCInventors: Nemanja Djuric, Vladan Radosavljevic, Thi Duong Nguyen, Tsung-Han Lin, Jeff Schneider
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Publication number: 20200074574Abstract: A transport system can manage an on-demand transportation service to connect available vehicles with users, and can compile ride history data for each user. The ride history data can indicate the contextual usage of the on-demand transportation service by the user. Based on the ride history data, the transport system can determine demographic and personal interest information of the respective user. The transport system may then personalize one or more ride characteristics of any ride requested by the user based on the demographic and personal interest information determined from the ride history of the user.Type: ApplicationFiled: November 8, 2019Publication date: March 5, 2020Inventors: Nemanja Djuric, Vladan Radosavljevic
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Patent number: 10579063Abstract: The present disclosure provides systems and methods for predicting the future locations of objects that are perceived by autonomous vehicles. An autonomous vehicle can include a prediction system that, for each object perceived by the autonomous vehicle, generates one or more potential goals, selects one or more of the potential goals, and develops one or more trajectories by which the object can achieve the one or more selected goals. The prediction systems and methods described herein can include or leverage one or more machine-learned models that assist in predicting the future locations of the objects. As an example, in some implementations, the prediction system can include a machine-learned static object classifier, a machine-learned goal scoring model, a machine-learned trajectory development model, a machine-learned ballistic quality classifier, and/or other machine-learned models. The use of machine-learned models can improve the speed, quality, and/or accuracy of the generated predictions.Type: GrantFiled: August 23, 2017Date of Patent: March 3, 2020Assignee: UATC, LLCInventors: Galen Clark Haynes, Ian Dewancker, Nemanja Djuric, Tzu-Kuo Huang, Tian Lan, Tsung-Han Lin, Micol Marchetti-Bowick, Vladan Radosavljevic, Jeff Schneider, Alexander David Styler, Neil Traft, Huahua Wang, Anthony Joseph Stentz
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Patent number: 10482559Abstract: A transport system can manage an on-demand transportation service to connect available vehicles with users, and can compile ride history data for each user. The ride history data can indicate the contextual usage of the on-demand transportation service by the user. Based on the ride history data, the transport system can determine demographic and personal interest information of the respective user. The transport system may then personalize one or more ride characteristics of any ride requested by the user based on the demographic and personal interest information determined from the ride history of the user.Type: GrantFiled: November 11, 2016Date of Patent: November 19, 2019Assignee: UATC, LLCInventors: Nemanja Djuric, Vladan Radosavljevic
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Publication number: 20190094858Abstract: A method for predicting one or more parking locations includes receiving feature map data associated with a feature map, the feature map comprises a plurality of elements of a matrix, each element of the matrix comprises the feature map data, and the feature map data is associated with one or more features of a road. The method includes processing the feature map data to produce artificial neuron data associated with one or more artificial neurons of one or more convolution layers. The method includes generating a prediction score for each element of the feature map based on the artificial neuron data, wherein the prediction score comprises a prediction of whether each element of the feature map comprises a parking location. The method includes outputting map data associated with a map, the map data is based on the one or more prediction scores associated with each element of the feature map.Type: ApplicationFiled: October 20, 2017Publication date: March 28, 2019Inventors: Vladan Radosavljevic, Jeff Schneider, Alexander Edward Chao
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Publication number: 20190049970Abstract: Systems and methods for predicting object motion and controlling autonomous vehicles are provided. In one example embodiment, a computer implemented method includes obtaining state data indicative of at least a current or a past state of an object that is within a surrounding environment of an autonomous vehicle. The method includes obtaining data associated with a geographic area in which the object is located. The method includes generating a combined data set associated with the object based at least in part on a fusion of the state data and the data associated with the geographic area in which the object is located. The method includes obtaining data indicative of a machine-learned model. The method includes inputting the combined data set into the machine-learned model. The method includes receiving an output from the machine-learned model. The output can be indicative of a plurality of predicted trajectories of the object.Type: ApplicationFiled: September 5, 2018Publication date: February 14, 2019Inventors: Nemanja Djuric, Vladan Radosavljevic, Thi Duong Nguyen, Tsung-Han Lin, Jeff Schneider, Henggang Cui, Fang-Chieh Chou, Tzu-Kuo Huang
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Publication number: 20190049987Abstract: Systems and methods for predicting object motion and controlling autonomous vehicles are provided. In one example embodiment, a computer implemented method includes obtaining state data indicative of at least a current or a past state of an object that is within a surrounding environment of an autonomous vehicle. The method includes obtaining data associated with a geographic area in which the object is located. The method includes generating a combined data set associated with the object based at least in part on a fusion of the state data and the data associated with the geographic area in which the object is located. The method includes obtaining data indicative of a machine-learned model. The method includes inputting the combined data set into the machine-learned model. The method includes receiving an output from the machine-learned model. The output can be indicative of a predicted trajectory of the object.Type: ApplicationFiled: October 13, 2017Publication date: February 14, 2019Inventors: Nemanja Djuric, Vladan Radosavljevic, Thi Duong Nguyen, Tsung-Han Lin, Jeff Schneider
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Publication number: 20190025841Abstract: The present disclosure provides systems and methods for predicting the future locations of objects that are perceived by autonomous vehicles. An autonomous vehicle can include a prediction system that, for each object perceived by the autonomous vehicle, generates one or more potential goals, selects one or more of the potential goals, and develops one or more trajectories by which the object can achieve the one or more selected goals. The prediction systems and methods described herein can include or leverage one or more machine-learned models that assist in predicting the future locations of the objects. As an example, in some implementations, the prediction system can include a machine-learned static object classifier, a machine-learned goal scoring model, a machine-learned trajectory development model, a machine-learned ballistic quality classifier, and/or other machine-learned models. The use of machine-learned models can improve the speed, quality, and/or accuracy of the generated predictions.Type: ApplicationFiled: August 23, 2017Publication date: January 24, 2019Inventors: Clark Haynes, Ian Dewancker, Nemanja Djuric, Tzu-Kuo Huang, Tian Lan, Hank Lin, Micol Marchetti-Bowick, Vladan Radosavljevic, Jeff Schneider, Alex Styler, Neil Traft, Huahua Wang, Tony Stentz
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Publication number: 20180137593Abstract: A transport system can manage an on-demand transportation service to connect available vehicles with users, and can compile ride history data for each user. The ride history data can indicate the contextual usage of the on-demand transportation service by the user. Based on the ride history data, the transport system can determine demographic and personal interest information of the respective user. The transport system may then personalize one or more ride characteristics of any ride requested by the user based on the demographic and personal interest information determined from the ride history of the user.Type: ApplicationFiled: November 11, 2016Publication date: May 17, 2018Inventors: Nemanja Djuric, Vladan Radosavljevic
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Publication number: 20170193037Abstract: Disclosed are systems and methods for improving interactions with and between computers in content searching, generating, 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 transform user search keywords into equivalent keyword formats commonly used and/or found within messaging platforms, and compile a data set from such information from which a search for content can be based. The present disclosure, therefore, provides systems and methods that augment users' search terms with terms found in users' mailboxes for purposes of searching for, identifying and communicating content that is relevant to those users.Type: ApplicationFiled: December 30, 2015Publication date: July 6, 2017Inventors: Varun Bhagwan, Blake Carpenter, Mihajlo Grbovic, Doug Sharp, Vladan Radosavljevic, Nemanja Djuric
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Publication number: 20160170982Abstract: The present teaching relates to joint representation of information. In one example, first and second pieces of information are received. Each of the first and second pieces of information relates to one word in a plurality of documents, one of the documents, or one of user to which the documents are given. A model for estimating feature vectors is obtained. The model includes a first neural network model based on a first order of words within one of the documents and a second neural network model based on a second order in which at least some of the documents are given. Based on the model, a first feature vector of the first piece of information and a second feature vector of the second piece of information are estimated. A similarity between the first and second pieces of information is determined based on a distance between the first and second feature vectors.Type: ApplicationFiled: December 16, 2014Publication date: June 16, 2016Inventors: Nemanja Djuric, Vladan Radosavljevic, Hao Wu, Mihajlo Grbovic, Narayan Bhamidipati
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Publication number: 20160125028Abstract: Systems and methods for rewriting query terms are disclosed. The system collects queries and query session data and separates the queries into sequences of queries having common sessions. The sequences of queries are then input into a deep learning network to build a multidimensional word vector in which related terms are nearer one another than unrelated terms. An input query is then received and the system matches the input query in the multidimensional word vector and rewrites the query using the nearest neighbors to the term of the input query.Type: ApplicationFiled: November 5, 2014Publication date: May 5, 2016Inventors: Fabrizio Silvestri, Mihajlo Grbovic, Narayan Bhamidipati, Vladan Radosavljevic, Nemanja Djuric
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Publication number: 20150379571Abstract: A system stored in a non-transitory medium executable by processor circuitry is provided for generating retargeting keywords based on distributed query word representations. The system includes one or more system databases storing historical web search data. Search retargeting circuitry receives requests to generate sets of retargeting keywords related to one or more categories of an advertisement campaign and pre-processing circuitry retrieves a set of historical web search data related to the one or more categories of the advertisement campaign. Modeling circuitry further applies one or more computational linguistic models to the retrieved set of historical web search data and generates distributed query word representations from the retrieved set of historical web search data. Keyword generator circuitry generates a list of retargeting keywords related to the one or more categories of the advertisement campaign using the generated distributed query word representations.Type: ApplicationFiled: June 30, 2014Publication date: December 31, 2015Applicant: YAHOO! Inc.Inventors: Mihajlo Grbovic, Nemanja Djuric, Vladan Radosavljevic, Narayan Bhamidipati