Patents by Inventor Manoj Kilaru
Manoj Kilaru 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: 20240143660Abstract: In various examples, an offline evaluation system obtains log data from a recommendation system and trains an imitation ranker using the log data. The imitation ranker generates a first result including a set of scores associated with document and rank pairs based on a query. The offline evaluation system may then determine a rank distribution indicating propensities associated with the document and rank pairs for a set of impressions which can be used to determine a value associated with the performance of the new recommendation system.Type: ApplicationFiled: November 1, 2022Publication date: May 2, 2024Inventors: Vishwa Vinay, Manoj Kilaru, David Thomas Arbour
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Patent number: 11868714Abstract: Methods and systems are provided for facilitating generation of fillable document templates. In embodiments, a document having a plurality of tokens is obtained. Using a machine learned model, a token state is identified for each token of the plurality of tokens. Each token state indicates whether a corresponding token is a static token that is to be included in a fillable document template or a dynamic token that is to be excluded in the fillable document template. Thereafter, a fillable document template corresponding with the document is generated, wherein for each dynamic token of the document, the fillable document template includes a fillable field corresponding to the respective dynamic token.Type: GrantFiled: February 28, 2022Date of Patent: January 9, 2024Assignee: Adobe Inc.Inventors: Natwar Modani, Muskan Agarwal, Vishesh Kaushik, Aparna Garimella, Akhash N A, Garvit Bhardwaj, Manoj Kilaru, Priyanshu Agarwal
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Patent number: 11836187Abstract: In implementations of systems for generating occurrence contexts for objects in digital content collections, a computing device implements a context system to receive context request data describing an object that is depicted with additional objects in digital images of a digital content collection. The context system generates relationship embeddings for the object and each of the additional objects using a representation learning model trained to predict relationships for objects. A relationship graph is formed for the object that includes a vertex for each relationship between the object and the additional objects indicated by the relationship embeddings. The context system clusters the vertices of the relationship graph into contextual clusters that each represent an occurrence context of the object in the digital images of the digital content collection.Type: GrantFiled: October 26, 2020Date of Patent: December 5, 2023Assignee: Adobe Inc.Inventors: Manoj Kilaru, Vishwa Vinay, Vidit Jain, Shaurya Goel, Ryan A. Rossi, Pratyush Garg, Nedim Lipka, Harkanwar Singh
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Publication number: 20230316124Abstract: In some embodiments, techniques for identifying bot activity are provided. For example, a process may involve receiving a plurality of samples, wherein each sample is a record of click activity; classifying the plurality of samples among a first class and a second class, using a machine learning model trained by a training process, to produce a corresponding plurality of classification predictions; filtering click activity data, based on information from the plurality of classification predictions, to produce filtered click activity data; and causing a user interface of a computing environment to be modified based on information from the filtered click activity data. The training process includes training the machine learning model to classify samples among the first and second classes, using a training set of samples of the first class, a training set of samples of the second class, and values of a topological loss function calculated based on the training sets.Type: ApplicationFiled: March 31, 2022Publication date: October 5, 2023Inventors: Gautam Choudhary, Sk Izajur Rahaman, Siba Smarak Panigrahi, Prithvi Bhutani, Manoj Kilaru, Kanishk Singh, Iftikhar Ahamath Burhanuddin, Aditi Singhania
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Patent number: 11769100Abstract: Systems and methods for data analytics are described. One or more embodiments of the present disclosure receive target time series data and candidate time series data, where the candidate time series data includes data corresponding to each of a plurality of candidate metrics, train a prediction network to predict the target time series data based on the candidate time series data by setting temporal attention weights corresponding to a plurality of rolling time windows and by setting candidate attention weights corresponding to the plurality of candidate metrics, identify a leading indicator metric for the target time series data from the plurality of candidate metrics based on the temporal attention weights and the candidate attention weights, and signal the leading indicator metric for the target time series data.Type: GrantFiled: May 25, 2021Date of Patent: September 26, 2023Assignee: ADOBE, INC.Inventors: Atanu Sinha, Manoj Kilaru, Iftikhar Ahamath Burhanuddin, Aneesh Shetty, Titas Chakraborty, Rachit Bansal, Tirupati Saketh Chandra, Fan Du, Aurghya Maiti, Saurabh Mahapatra
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Publication number: 20230274084Abstract: Methods and systems are provided for facilitating generation of fillable document templates. In embodiments, a document having a plurality of tokens is obtained. Using a machine learned model, a token state is identified for each token of the plurality of tokens. Each token state indicates whether a corresponding token is a static token that is to be included in a fillable document template or a dynamic token that is to be excluded in the fillable document template. Thereafter, a fillable document template corresponding with the document is generated, wherein for each dynamic token of the document, the fillable document template includes a fillable field corresponding to the respective dynamic token.Type: ApplicationFiled: February 28, 2022Publication date: August 31, 2023Inventors: Natwar Modani, Muskan Agarwal, Vishesh Kaushik, Aparna Garimella, Akhash N A, Garvit Bhardwaj, Manoj Kilaru, Priyanshu Agarwal
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Publication number: 20230262237Abstract: Systems and methods for image processing are described. The systems and methods include receiving a plurality of frames of a video at an edge device, wherein the video depicts an action that spans the plurality of frames, compressing, using an encoder network, each of the plurality of frames to obtain compressed frame features, wherein the compressed frame features include fewer data bits than the plurality of frames of the video, classifying, using a classification network, the compressed frame features at the edge device to obtain action classification information corresponding to the action in the video, and transmitting the action classification information from the edge device to a central server.Type: ApplicationFiled: February 15, 2022Publication date: August 17, 2023Inventors: Subrata Mitra, Aniruddha Mahapatra, Kuldeep Sharad Kulkarni, Abhishek Yadav, Abhijith Kuruba, Manoj Kilaru
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Patent number: 11663497Abstract: A method includes accessing a subject entity and a subject relation of a focal platform and accessing a knowledge graph representative of control performance data. Further, the method includes computing a set of ranked target entities that cause the subject entity based on the subject relation or are an effect of the subject entity based on the subject relation. Computing the set of ranked target entities is performed using relational hops from the subject entity within the knowledge graph performed using the subject relation and reward functions. The method also includes transmitting the set of ranked target entities to the focal platform. The set of ranked target entities is usable for modifying a user interface of an interactive computing environment provided by the focal platform.Type: GrantFiled: April 19, 2019Date of Patent: May 30, 2023Assignee: ADOBE INC.Inventors: Atanu Sinha, Prakhar Gupta, Manoj Kilaru, Madhav Goel, Deepanshu Bansal, Deepali Jain, Aniket Raj
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Publication number: 20220383224Abstract: Systems and methods for data analytics are described. One or more embodiments of the present disclosure receive target time series data and candidate time series data, where the candidate time series data includes data corresponding to each of a plurality of candidate metrics, train a prediction network to predict the target time series data based on the candidate time series data by setting temporal attention weights corresponding to a plurality of rolling time windows and by setting candidate attention weights corresponding to the plurality of candidate metrics, identify a leading indicator metric for the target time series data from the plurality of candidate metrics based on the temporal attention weights and the candidate attention weights, and signal the leading indicator metric for the target time series data.Type: ApplicationFiled: May 25, 2021Publication date: December 1, 2022Inventors: Atanu Sinha, Manoj Kilaru, Iftikhar Ahamath Burhanuddin, Aneesh Shetty, Titas Chakraborty, Rachit Bansal, Tirupati Saketh Chandra, Fan Du, Aurghya Maiti, Saurabh Mahapatra
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Publication number: 20220129498Abstract: In implementations of systems for generating occurrence contexts for objects in digital content collections, a computing device implements a context system to receive context request data describing an object that is depicted with additional objects in digital images of a digital content collection. The context system generates relationship embeddings for the object and each of the additional objects using a representation learning model trained to predict relationships for objects. A relationship graph is formed for the object that includes a vertex for each relationship between the object and the additional objects indicated by the relationship embeddings. The context system clusters the vertices of the relationship graph into contextual clusters that each represent an occurrence context of the object in the digital images of the digital content collection.Type: ApplicationFiled: October 26, 2020Publication date: April 28, 2022Applicant: Adobe Inc.Inventors: Manoj Kilaru, Vishwa Vinay, Vidit Jain, Shaurya Goel, Ryan A. Rossi, Pratyush Garg, Nedim Lipka, Harkanwar Singh
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Publication number: 20200334545Abstract: A method includes accessing a subject entity and a subject relation of a focal platform and accessing a knowledge graph representative of control performance data. Further, the method includes computing a set of ranked target entities that cause the subject entity based on the subject relation or are an effect of the subject entity based on the subject relation. Computing the set of ranked target entities is performed using relational hops from the subject entity within the knowledge graph performed using the subject relation and reward functions. The method also includes transmitting the set of ranked target entities to the focal platform. The set of ranked target entities is usable for modifying a user interface of an interactive computing environment provided by the focal platform.Type: ApplicationFiled: April 19, 2019Publication date: October 22, 2020Inventors: Atanu Sinha, Prakhar Gupta, Manoj Kilaru, Madhav Goel, Deepanshu Bansal, Deepali Jain, Aniket Raj
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Publication number: 20190147384Abstract: Embodiments of the present invention provide systems, methods, and computer storage media are generally directed to facilitating generation of contributor ratings. In one embodiment, upon obtaining content contributed by a contributor, a particular skill(s) associated with the contributed content is identified. An event-level rating indicating a value of the contributed content in relation to the particular skill can be determined based on, for example, context and sentiment associated with the contributed content. Such an event-level rating, among others, can be used to generate a contributor rating for the particular skill. The contributor rating for the particular skill can then be provided, for example, for presentation in association with the content contributed by the contributor.Type: ApplicationFiled: November 16, 2017Publication date: May 16, 2019Inventors: Natwar Modani, Kundan Krishna, Harsh Khetan, Manoj Kilaru