Patents by Inventor Manish Anand Bhide

Manish Anand Bhide 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).

  • Publication number: 20210295204
    Abstract: Embodiments are disclosed for a method for machine-learning model accuracy. The method includes generating prediction training data based on training predictions and corresponding probabilities of the training predictions. A classifier of a machine-learning model generates the training predictions. The method also includes training a prediction accuracy model to determine whether the training predictions generated by the machine-learning model are correct. Additionally, the method includes generating predictions in response to corresponding client transactions for the machine-learning model. Further, the method includes determining whether the predictions are accurate using the prediction accuracy model. Also, the method includes providing client predictions corresponding to the client transactions based on the determination.
    Type: Application
    Filed: March 19, 2020
    Publication date: September 23, 2021
    Inventors: Manish Anand Bhide, Venkata R. Madugundu, HARIVANSH KUMAR, PREM PIYUSH GOYAL
  • Publication number: 20210287131
    Abstract: A system includes a memory having instructions therein and at least one processor in communication with the memory. The at least one processor is configured to execute the instructions to run a machine learning base model on input data to generate base model prediction data and run a machine learning error prediction model on the input data to generate error prediction data. The at least one processor is configured to execute the instructions to generate predicted correct base model prediction data based on the base model prediction data and the error prediction data. The at least one processor is configured to execute the instructions to generate confusion values data based on the base model prediction data and the predicted correct base model prediction data. The at least one processor is also configured to execute the instructions to generate base model accuracy fairness metrics data based on the confusion values data.
    Type: Application
    Filed: March 10, 2020
    Publication date: September 16, 2021
    Inventors: Manish Anand Bhide, Madhavi Katari, Ravi Chandra Chamarthy, Swapna Somineni
  • Publication number: 20210286945
    Abstract: According to one embodiment of the present invention, a system for modifying content associated with an item comprises at least one processor. Features of interest of the item to a plurality of different groups are determined based on user comments produced by members of the plurality of different groups. The members within each group have a common characteristic. The features of interest to each group within the content associated with the item are identified, and the content associated with the item is modified by balancing the features of interest to the plurality of different groups within the content associated with the item. Embodiments of the present invention further include a method and computer program product for modifying content associated with an item in substantially the same manner described above.
    Type: Application
    Filed: March 13, 2020
    Publication date: September 16, 2021
    Inventors: Seema Nagar, Kuntal Dey, Nishtha Madaan, Manish Anand Bhide, Sameep Mehta, Diptikalyan Saha
  • Patent number: 11120204
    Abstract: An article is automatically augmented. The article and one or more comments are received. Comment elements are extracted from the one or more comments, and article elements are extracted from the article. Alignment scores are generated for comment-article pairs based on the extracted comment and article elements. Further, it is determined that at least one comment-article pair has an alignment score at or above a threshold alignment score. At least one augmentation feature is then generated.
    Type: Grant
    Filed: July 15, 2019
    Date of Patent: September 14, 2021
    Assignee: International Business Machines Corporation
    Inventors: Manish Anand Bhide, Nishtha Madaan, Seema Nagar, Sameep Mehta, Kuntal Dey
  • Publication number: 20210279607
    Abstract: A computer-implemented method according to one embodiment includes identifying an occurrence of accuracy drift by a trained model; identifying data associated with the accuracy drift, utilizing a drift detection model (DDM) constructed for the trained model; applying the data associated with the accuracy drift to a decision tree to determine a feature space and specific subset of the data causing the accuracy drift; analyzing a distribution of features within the feature space for the specific subset of the data causing the accuracy drift to determine specific features of the data causing the accuracy drift; and returning the specific features of the data causing the accuracy drift.
    Type: Application
    Filed: March 9, 2020
    Publication date: September 9, 2021
    Inventors: Manish Anand Bhide, Pranay Kumar Lohia, Diptikalyan Saha, Madhavi Katari
  • Patent number: 11113643
    Abstract: Managing notifications is provided. Personal monitoring system inputs corresponding to each member of a defined group performing a common task are contextually analyzed to identify a notification sequence for each respective member enabling task performance in a synchronized manner. Progress of each respective member while performing activities corresponding to the common task is analyzed using the personal monitoring system inputs to enable dynamic modification of the notification sequence and content to the members in accordance with the progress. Existence of any problem is identified during performance of activities corresponding to the common task to accordingly modify the notification sequence and content to target members for mitigation of an existing problem.
    Type: Grant
    Filed: January 3, 2020
    Date of Patent: September 7, 2021
    Assignee: International Business Machines Corporation
    Inventors: Manish Anand Bhide, Sarbajit K. Rakshit, Madhavi Katari, Seema Nagar, Kuntal Dey
  • Patent number: 11106864
    Abstract: An article is automatically augmented. The article and one or more comments are received. Comment elements are extracted from the one or more comments, and article elements are extracted from the article. Alignment scores are generated for comment-article pairs based on the extracted comment and article elements. Further, it is determined that at least one comment-article pair has an alignment score at or above a threshold alignment score. At least one augmentation feature is then generated.
    Type: Grant
    Filed: March 22, 2019
    Date of Patent: August 31, 2021
    Assignee: International Business Machines Corporation
    Inventors: Manish Anand Bhide, Nishtha Madaan, Seema Nagar, Sameep Mehta, Kuntal Dey
  • Patent number: 11086754
    Abstract: Approaches presented herein enable optimization of a developing application to a user base. More specifically, application-centric data is gathered during a cultivation phase of the developing application. Substantially concurrently with the cultivation phase of the developing application, the application-centric data is analyzed according to static code of the developing application, a testing of the developing application, or a user experience (UX) design of the developing application. A machine learning model is applied to the analyzed application-centric data. This machine learning model is trained on historic application feedback data from applications available to the user base. Based on the machine learning model, a recommended change to optimize the developing application to the user base is generated.
    Type: Grant
    Filed: July 2, 2019
    Date of Patent: August 10, 2021
    Assignee: International Business Machines Corporation
    Inventors: Manish Anand Bhide, Vijay Kumar Ananthapur Bache, Srinivas Chebolu, Jhilam Bera
  • Publication number: 20210209540
    Abstract: Managing notifications is provided. Personal monitoring system inputs corresponding to each member of a defined group performing a common task are contextually analyzed to identify a notification sequence for each respective member enabling task performance in a synchronized manner. Progress of each respective member while performing activities corresponding to the common task is analyzed using the personal monitoring system inputs to enable dynamic modification of the notification sequence and content to the members in accordance with the progress. Existence of any problem is identified during performance of activities corresponding to the common task to accordingly modify the notification sequence and content to target members for mitigation of an existing problem.
    Type: Application
    Filed: January 3, 2020
    Publication date: July 8, 2021
    Inventors: Manish Anand Bhide, Sarbajit K. Rakshit, Madhavi Katari, Seema Nagar, Kuntal Dey
  • Publication number: 20210158102
    Abstract: Methods, systems, and computer program products for determining data representative of bias within a model are provided herein. A computer-implemented method includes obtaining a first dataset on which a model was trained, wherein the first dataset contains protected attributes, and a second dataset on which the model was trained, wherein the protected attributes have been removed from the second dataset; identifying, for each of the one or more protected attributes in the first dataset, one or more attributes in the second dataset correlated therewith; determining bias among at least a portion of the identified correlated attributes; and outputting, to at least one user, identifying information pertaining to the one or more instances of bias.
    Type: Application
    Filed: November 21, 2019
    Publication date: May 27, 2021
    Inventors: Pranay Kumar Lohia, Diptikalyan Saha, Manish Anand Bhide, Sameep Mehta
  • Publication number: 20210158076
    Abstract: Methods, systems, and computer program products for determining model-related bias associated with training data are provided herein. A computer-implemented method includes obtaining, via execution of a first model, class designations attributed to data points used to train the first model; identifying any of the data points associated with an inaccurate class designation and/or a low-confidence class designation; training a second model using the data points from the dataset, but excluding the identified data points; determining bias related to at least a portion of those data points used to train the second model by: modifying one or more of the data points used to train the second model; executing the first model using the modified data points; and identifying a change to one or more class designations attributed to the modified data points as compared to before the modifying; and outputting identifying information pertaining to the determined bias.
    Type: Application
    Filed: November 21, 2019
    Publication date: May 27, 2021
    Inventors: Pranay Kumar Lohia, Diptikalyan Saha, Manish Anand Bhide, Sameep Mehta
  • Publication number: 20210097052
    Abstract: Methods, systems, and computer program products for domain aware explainable anomaly and drift detection for multi-variate raw data using a constraint repository are provided herein. A computer-implemented method includes obtaining a set of data and information indicative of a domain of said set of data; obtaining constraints from a domain-indexed constraint repository based on said set of data and said information, wherein the domain-indexed constraint repository comprises a knowledge graph having a plurality of nodes, wherein each node comprises an attribute associated with at least one of a plurality of domains and constraints corresponding to the attribute; detecting anomalies in said set of data based on whether portions of said set of data violate said retrieved constraints; generating an explanation corresponding to each of the anomalies that describe the attributes corresponding to the violated constraints; and outputting an indication of the anomalies and the corresponding explanation.
    Type: Application
    Filed: September 27, 2019
    Publication date: April 1, 2021
    Inventors: Sandeep Hans, Samiulla Zakir Hussain Shaikh, Rema Ananthanarayanan, Diptikalyan Saha, Aniya Aggarwal, Gagandeep Singh, Pranay Kumar Lohia, Manish Anand Bhide, Sameep Mehta
  • Publication number: 20210035014
    Abstract: Aspects of the present invention provide an approach for reducing bias in active learning. In an embodiment, a data point is selected from a training dataset for a current training iteration while monitoring for data bias at each addition of data to a virtual training dataset. In addition, a machine learning model is examined for bias after adding the selected data point to the virtual training dataset. When data bias and/or model bias is detected, the data point is considered for potential label modification. The selected data point is modified and, if the raw value of the modified data point is within a predefined tolerance and within a bin of a desired class, the modified data point having a label of the target class is retained. Otherwise, it can be discarded.
    Type: Application
    Filed: July 31, 2019
    Publication date: February 4, 2021
    Inventors: Kuntal Dey, Sameep Mehta, Manish Anand Bhide
  • Publication number: 20210004311
    Abstract: Approaches presented herein enable optimization of a developing application to a user base. More specifically, application-centric data is gathered during a cultivation phase of the developing application. Substantially concurrently with the cultivation phase of the developing application, the application-centric data is analyzed according to static code of the developing application, a testing of the developing application, or a user experience (UX) design of the developing application. A machine learning model is applied to the analyzed application-centric data. This machine learning model is trained on historic application feedback data from applications available to the user base. Based on the machine learning model, a recommended change to optimize the developing application to the user base is generated.
    Type: Application
    Filed: July 2, 2019
    Publication date: January 7, 2021
    Inventors: Manish Anand Bhide, Vijay Kumar Ananthapur Bache, Srinivas Chebolu, Jhilam Bera
  • Publication number: 20200401565
    Abstract: In an approach for automatically ranking and routing data quality remediation tasks, a processor analyzes a data set ingested by a repository to produce a set of data quality problems. A processor computes a score for each data quality problem of the set of data quality problems. A processor identifies a route to send each data quality problem of the set of data quality problems. A processor exports each data quality problem according to the score and the route.
    Type: Application
    Filed: June 20, 2019
    Publication date: December 24, 2020
    Inventors: Yannick Saillet, Namit Kabra, Manish Anand Bhide
  • Publication number: 20200372398
    Abstract: A method, computer system, and a computer program product for utilizing provenance data to improve machine learning is provided. Embodiments of the present invention may include collecting provenance data. Embodiments of the present invention may include identifying model quality improvements based on the collected provenance data. Embodiments of the present invention may include identifying related models based on the collected provenance data. Embodiments of the present invention may include recommending model quality improvements to a user.
    Type: Application
    Filed: May 22, 2019
    Publication date: November 26, 2020
    Inventors: Samiulla Zakir Hussain Shaikh, HIMANSHU GUPTA, Rajmohan Chandrahasan, Sameep Mehta, Manish Anand Bhide
  • Publication number: 20200372101
    Abstract: A processor may receive a record. The record may include one or more segments of text. The processor may automatically generate a first summary of the record. The processor may determine an overall bias of the first summary. The overall bias of the first summary may be identified from one or more instances of bias in the first summary. The processor may generate a second summary of the record. The second summary of the record may include an indicator of the overall bias of the first summary. The indicator may include a description of a type of overall bias of the first summary and a numerical value of the overall bias of the first summary. The processor may determine an overall bias of the second summary. The processor may display the second summary of the record to a user.
    Type: Application
    Filed: May 23, 2019
    Publication date: November 26, 2020
    Inventors: Manish Anand Bhide, Kuntal Dey, Nishtha Madaan, Seema Nagar, Sameep Mehta
  • Publication number: 20200372056
    Abstract: A processor may receive a record. The record may include one or more segments of text. The processor may tag each segment of text with an indicator. The indicator may denote a specific instance of bias in each of a respective segment of text. The processor may automatically generate a summary of the record. The summary of the record may include a set of segments of text. The set of segments of text may have a different overall bias than the record. The processor may display the summary of the record to a user.
    Type: Application
    Filed: May 23, 2019
    Publication date: November 26, 2020
    Inventors: Manish Anand Bhide, Kuntal Dey, Nishtha Madaan, Seema Nagar, Sameep Mehta
  • Publication number: 20200356580
    Abstract: Relationship discovery can include receiving at a first mobile device a pair of ultrasonic signals conveyed at different frequencies from a second mobile device. The pair of ultrasonic signals can convey, respectively, a second user's contact information in an encrypted form and a key indicator. A contact number can be selected from a first user's contact list electronically stored on the first mobile device. The contact number can be selected based on the key indicator. A mutual contact can be identified in response to decrypting the second user's contact information using the contact number as a decryption key.
    Type: Application
    Filed: May 7, 2019
    Publication date: November 12, 2020
    Inventors: Saravanan Sadacharam, Manish Anand Bhide, Vijay Ekambaram, Vijay Kumar Ananthapur Bache
  • Publication number: 20200302005
    Abstract: An article is automatically augmented. The article and one or more comments are received. Comment elements are extracted from the one or more comments, and article elements are extracted from the article. Alignment scores are generated for comment-article pairs based on the extracted comment and article elements. Further, it is determined that at least one comment-article pair has an alignment score at or above a threshold alignment score. At least one augmentation feature is then generated.
    Type: Application
    Filed: March 22, 2019
    Publication date: September 24, 2020
    Inventors: Manish Anand Bhide, Nishtha Madaan, Seema Nagar, Sameep Mehta, Kuntal Dey