Patents by Inventor Ishan JINDAL

Ishan JINDAL 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).

  • Patent number: 12174913
    Abstract: Systems and techniques that facilitate parameterized neighborhood memory adaptation for semantic role labeling are provided. In various embodiments, a system can comprise a receiver component that can access a semantic role labeling model trained on a training dataset. In various aspects, the system can further comprise an execution component that can retrain a labeler of the semantic role labeling model based on a set of neighborhood parameters learned from the training dataset. In various instances, the execution component can execute, after retraining, the semantic role labeling model on an inputted sentence.
    Type: Grant
    Filed: April 29, 2021
    Date of Patent: December 24, 2024
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Ishan Jindal, Yunyao Li, Siddhartha Brahma, Huaiyu Zhu
  • Patent number: 12045573
    Abstract: One or more systems, devices, computer program products and/or computer-implemented methods of use provided herein relate to regularizing semantic similarity relationships relative to a pair of languages. A system can comprise a memory that stores computer executable components, and a processor that executes the computer executable components stored in the memory, wherein the computer executable components comprise a computation component that generates a transformation comprising a semantic similarity relationship between detected semantic labels of a pair of languages.
    Type: Grant
    Filed: October 28, 2021
    Date of Patent: July 23, 2024
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Ishan Jindal, Yunyao Li, Siddhartha Brahma, Huaiyu Zhu
  • Patent number: 11948387
    Abstract: Systems and methods for training an object detection network are described. Embodiments train an object detection network using a labeled training set, wherein each element of the labeled training set includes an image and ground truth labels for object instances in the image, predict annotation data for a candidate set of unlabeled data using the object detection network, select a sample image from the candidate set using a policy network, generate a labeled sample based on the selected sample image and the annotation data, wherein the labeled sample includes labels for a plurality of object instances in the sample image, and perform additional training on the object detection network based at least in part on the labeled sample.
    Type: Grant
    Filed: February 8, 2021
    Date of Patent: April 2, 2024
    Assignee: ADOBE INC.
    Inventors: Sumit Shekhar, Bhanu Prakash Reddy Guda, Ashutosh Chaubey, Ishan Jindal, Avneet Jain
  • Publication number: 20230135140
    Abstract: One or more systems, devices, computer program products and/or computer-implemented methods of use provided herein relate to regularizing semantic similarity relationships relative to a pair of languages. A system can comprise a memory that stores computer executable components, and a processor that executes the computer executable components stored in the memory, wherein the computer executable components comprise a computation component that generates a transformation comprising a semantic similarity relationship between detected semantic labels of a pair of languages.
    Type: Application
    Filed: October 28, 2021
    Publication date: May 4, 2023
    Inventors: Ishan Jindal, Yunyao Li, Siddhartha Brahma, Huaiyu Zhu
  • Patent number: 11536582
    Abstract: Systems and methods are provided for estimating travel time and distance. Such method may comprise obtaining a vehicle trip dataset comprising an origin, a destination, a time-of-day, a trip time, and a trip distance associated with each of a plurality of trips, and training a neural network model with the vehicle trip dataset to obtain a trained model. The neural network model may comprise a first module and a second module, the first module may comprise a first number of neuron layers, the first module may be configured to obtain the origin and the destination as first inputs to estimate a travel distance, the second module may comprise a second number of neuron layers, and the second module may be configured to obtain the information of a last layer of the first module and the time-of-day as second inputs to estimate a travel time.
    Type: Grant
    Filed: August 10, 2017
    Date of Patent: December 27, 2022
    Assignee: Beijing DiDi Infinity Technology and Development Co., Ltd.
    Inventors: Ishan Jindal, Zhiwei Qin, Xuewen Chen
  • Publication number: 20220366188
    Abstract: Systems and techniques that facilitate parameterized neighborhood memory adaptation for semantic role labeling are provided. In various embodiments, a system can comprise a receiver component that can access a semantic role labeling model trained on a training dataset. In various aspects, the system can further comprise an execution component that can retrain a labeler of the semantic role labeling model based on a set of neighborhood parameters learned from the training dataset. In various instances, the execution component can execute, after retraining, the semantic role labeling model on an inputted sentence.
    Type: Application
    Filed: April 29, 2021
    Publication date: November 17, 2022
    Inventors: Ishan Jindal, Yunyao Li, Siddhartha Brahma, Huaiyu Zhu
  • Publication number: 20220253630
    Abstract: Systems and methods for training an object detection network are described. Embodiments train an object detection network using a labeled training set, wherein each element of the labeled training set includes an image and ground truth labels for object instances in the image, predict annotation data for a candidate set of unlabeled data using the object detection network, select a sample image from the candidate set using a policy network, generate a labeled sample based on the selected sample image and the annotation data, wherein the labeled sample includes labels for a plurality of object instances in the sample image, and perform additional training on the object detection network based at least in part on the labeled sample.
    Type: Application
    Filed: February 8, 2021
    Publication date: August 11, 2022
    Inventors: Sumit Shekhar, Bhanu Prakash Reddy Guda, Ashutosh Chaubey, Ishan Jindal, Avneet Jain
  • Publication number: 20210231454
    Abstract: Systems and methods are provided for estimating travel time and distance. Such method may comprise obtaining a vehicle trip dataset comprising an origin, a destination, a time-of-day, a trip time, and a trip distance associated with each of a plurality of trips, and training a neural network model with the vehicle trip dataset to obtain a trained model. The neural network model may comprise a first module and a second module, the first module may comprise a first number of neuron layers, the first module may be configured to obtain the origin and the destination as first inputs to estimate a travel distance, the second module may comprise a second number of neuron layers, and the second module may be configured to obtain the information of a last layer of the first module and the time-of-day as second inputs to estimate a travel time.
    Type: Application
    Filed: August 10, 2017
    Publication date: July 29, 2021
    Inventors: Ishan JINDAL, Zhiwei QIN, Xuewen CHEN
  • Patent number: 10989546
    Abstract: A method may comprise recursively performing: (1) providing one or more states of a simulation environment to a simulated vehicle, and the states comprise a first current time and a first current location of the simulated vehicle; (2) obtaining an action by the simulated vehicle when the simulated vehicle has reached a milestone, wherein: the action is selected from: waiting at the first current location of the simulated vehicle, picking up a passenger group A at an origin of passenger group A's transportation, and dropping off a passenger group B at a destination of passenger group B's transportation, and the milestone is an origin or a destination of any passenger group's transportation; (3) determining a reward to the simulated vehicle for the action; and (4) updating the one or more states based on the action to obtain one or more updated states for providing to the simulated vehicle.
    Type: Grant
    Filed: May 3, 2018
    Date of Patent: April 27, 2021
    Assignee: Beijing DiDi Infinity Technology and Development Co., Ltd.
    Inventors: Zhiwei Qin, Ishan Jindal, Xuewen Chen
  • Patent number: 10635764
    Abstract: A method for providing vehicle navigation simulation environment may comprise recursively performing steps (1)-(4) for a time period: (1) providing one or more states of a simulation environment to a simulated agent, wherein: the simulated agent comprises a simulated vehicle, and the states comprise a first current time and a first current location of the simulated vehicle; (2) obtaining an action by the simulated vehicle when the simulated vehicle has no passenger, wherein the action is selected from: waiting at the first current location of the simulated vehicle, and transporting M passenger groups; (3) determining a reward to the simulated vehicle for the action; and (4) updating the one or more states based on the action to obtain one or more updated states for providing to the simulated vehicle, wherein: the updated states comprise a second current time and a second current location of the simulated vehicle.
    Type: Grant
    Filed: May 3, 2018
    Date of Patent: April 28, 2020
    Assignee: DiDi Research America, LLC
    Inventors: Zhiwei Qin, Ishan Jindal, Xuewen Chen
  • Publication number: 20190339087
    Abstract: A method for operating a ride-share-enabled vehicle includes determining a target location of the ride-share-enabled vehicle, determining a ride-sharing policy algorithm to determine a behavior of the ride-share-enabled vehicle including whether to accept a multiple shared ride or maintain a single shared ride and a route of the multiple shared ride, if any, based on the determined target location of the ride-share-enabled vehicle, determining a behavior of the ride-share-enabled vehicle based on a current location of the ride-share-enabled vehicle and the determined ride-sharing policy algorithm, and causing the ride-share-enabled vehicle to be operated according to the determined behavior of the ride-share-enabled vehicle.
    Type: Application
    Filed: May 3, 2018
    Publication date: November 7, 2019
    Inventors: Ishan JINDAL, Zhiwei QIN, Xuewen CHEN, Matthew NOKLEBY, Jieping YE
  • Publication number: 20190340315
    Abstract: A method for providing vehicle navigation simulation environment may comprise recursively performing steps (1)-(4) for a time period: (1) providing one or more states of a simulation environment to a simulated agent, wherein: the simulated agent comprises a simulated vehicle, and the states comprise a first current time and a first current location of the simulated vehicle; (2) obtaining an action by the simulated vehicle when the simulated vehicle has no passenger, wherein the action is selected from: waiting at the first current location of the simulated vehicle, and transporting M passenger groups; (3) determining a reward to the simulated vehicle for the action; and (4) updating the one or more states based on the action to obtain one or more updated states for providing to the simulated vehicle, wherein: the updated states comprise a second current time and a second current location of the simulated vehicle.
    Type: Application
    Filed: May 3, 2018
    Publication date: November 7, 2019
    Inventors: Zhiwei QIN, Ishan JINDAL, Xuewen CHEN
  • Publication number: 20190339086
    Abstract: A method may comprise recursively performing: (1) providing one or more states of a simulation environment to a simulated vehicle, and the states comprise a first current time and a first current location of the simulated vehicle; (2) obtaining an action by the simulated vehicle when the simulated vehicle has reached a milestone, wherein: the action is selected from: waiting at the first current location of the simulated vehicle, picking up a passenger group A at an origin of passenger group A's transportation, and dropping off a passenger group B at a destination of passenger group B's transportation, and the milestone is an origin or a destination of any passenger group's transportation; (3) determining a reward to the simulated vehicle for the action; and (4) updating the one or more states based on the action to obtain one or more updated states for providing to the simulated vehicle.
    Type: Application
    Filed: May 3, 2018
    Publication date: November 7, 2019
    Inventors: Zhiwei QIN, Ishan JINDAL, Xuewen CHEN