Patents by Inventor Neelakantan Sundaresan

Neelakantan Sundaresan 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).

  • Updating of stored item data via a remote computing system
    Patent number: 11562419
    Abstract: In various example embodiments, a system and method for an electronic commerce file system are provided. In example embodiments, a selection of an item contained in a folder of an electronic commerce file system is received. The item is offered for sale by an electronic commerce provider, and the electronic commerce file system resides locally on a client device. Based on a type of the folder, a set of actions are provided for selection, with the set of actions to be performed with respect to the item. A selection of an action to be performed with respect to the item is received. The action is performed with respect to the item, with the action being performed between the electronic commerce file system and the electronic commerce provider via a network.
    Type: Grant
    Filed: May 22, 2020
    Date of Patent: January 24, 2023
    Assignee: EBAY INC.
    Inventors: Sandra Lynn Godsey, Neelakantan Sundaresan
  • Systems and methods to fit an image of an inventory part
    Patent number: 11551490
    Abstract: Systems and methods to fit an image of an inventory part are described. In one aspect, a method includes receiving images of items over a computer network from a server, capturing a live video image of an object using a camera, playing the live video of the object on an electronic display, and continually refitting an image of a first item from the received images of items to the object as the object changes perspective in the video by applying an affine transformation to the image of the first item.
    Type: Grant
    Filed: October 2, 2018
    Date of Patent: January 10, 2023
    Assignee: eBay Inc.
    Inventors: Anurag Bhardwaj, Robinson Piramuthu, Neelakantan Sundaresan
  • AUTOMATED FINE-TUNING AND DEPLOYMENT OF PRE-TRAINED DEEP LEARNING MODELS
    Publication number: 20220398462
    Abstract: A cloud platform includes several web services that facilitate the automated tuning and deployment of pre-trained deep learning models configured for software engineering tasks. The automated tuning and deployment allow a developer to fine-tune a pre-existing model without having access to the parameters of the pre-existing and the fine-tuned model in a manner that does not require user management input. The cloud platform provides a set of files for each pre-trained models used to automatically build a fine-tuning infrastructure to fine-tune a model and a deployment infrastructure that deploys the fine-tuned model without requiring user input.
    Type: Application
    Filed: June 14, 2021
    Publication date: December 15, 2022
    Inventors: COLIN BRUCE CLEMENT, SHAO KUN DENG, DAWN DRAIN, NEELAKANTAN SUNDARESAN, ALEXEY SVYATKOVSKIY, YIDING TIAN, MICHELE TUFANO, PAUL AN-CHIEH WANG, CHEN WU, DONGJIANG YOU
  • CODE GENERATION WITH REINFORCEMENT LEARNING
    Publication number: 20220398071
    Abstract: A code generation system uses a non-terminal expansion model and a non-terminal selector model to generate a code sketch to complete a partially-formed source code snippet. The non-terminal expansion model is a neural transformer model trained on a supervised dataset through reinforcement learning to learn to predict the production rule to expand for a given non-terminal symbol. The non-terminal selector model is trained through reinforcement learning to predict the non-terminal symbol to expand given a partial-code state. The models are used in a two-step beam search to generate the top candidate code sketches, where a candidate code sketch may contain a hole that represents an unexpanded non-terminal symbol.
    Type: Application
    Filed: August 16, 2021
    Publication date: December 15, 2022
    Inventors: MILTIADIS ALLAMANIS, DAYA GUO, NEELAKANTAN SUNDARESAN, ALEXEY SVYATKOVSKIY
  • Dynamic experimentation evaluation system
    Patent number: 11526421
    Abstract: A dynamic experimentation evaluation system provides a framework in which a continuous stream of metric data is monitored to establish a causal relationship between changes in a software program and the effect of user-observable behavior. In one aspect, an A/B test is performed continuously on a stream of metric data representing the usage of a control version of software product and the usage of a treatment version of the software product. A sequential probability ratio test (SPRT) is used as the test statistic to determine when to terminate the test and produce results within a specific confidence interval and controlled error rate.
    Type: Grant
    Filed: September 14, 2018
    Date of Patent: December 13, 2022
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC.
    Inventors: Neelakantan Sundaresan, Cenzhuo Yao
  • Automated program repair tool
    Patent number: 11526424
    Abstract: An automated program repair tool utilizes a neural transformer model with attention to predict the contents of a bug repair in the context of source code having a bug of an identified bug type. The neural transformer model is trained on a large unsupervised corpus of source code using a span-masking denoising optimization objective, and fine-tuned on a large supervised dataset of triplets containing a bug-type annotation, software bug, and repair. The bug-type annotation is derived from an interprocedural static code analyzer. A bug type edit centroid is computed for each bug type and used in the inference decoding phase to generate the bug repair.
    Type: Grant
    Filed: June 10, 2020
    Date of Patent: December 13, 2022
    Assignee: MICROSOFT TECHNOLOGY LICENSING LLC.
    Inventors: Shao Kun Deng, Neelakantan Sundaresan, Alexey Svyatkovskiy, Michele Tufano
  • Cloud resource management using machine learning
    Patent number: 11526370
    Abstract: A cloud resource management system trains, through ensemble learning, multiple time series forecasting models to forecast a future idle time of a virtual machine operating on a cloud computing service. The models are trained on historical usage and metric data of the virtual machine. The metric data includes CPU usage, disk usage and network usage. A select one of the models having the best accuracy for a target virtual machine is used in a production run to predict when the virtual machine will be idle. At this time, the virtual machine may be automatically shutdown in order to reduce the expense associated with the continued operation of the virtual machine.
    Type: Grant
    Filed: March 10, 2019
    Date of Patent: December 13, 2022
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC.
    Inventors: Yiping Dou, Tanmayee Prakash Kamath, Arun Ramanathan Chandrasekhar, Claude Remillard, Mark Steven Schnitzer, Balan Subramanian, Neelakantan Sundaresan, Yijin Wei
  • Transfer learning system for automated software engineering tasks
    Patent number: 11521075
    Abstract: A transfer learning system is used for the development of neural transformer models pertaining to software engineering tasks. The transfer learning system trains source code domain neural transformer models with attention in various configurations on a large corpus of unsupervised training dataset of source code programs and/or source code-related natural language text. A web service provides the trained models for use in developing a model that may be fine-tuned on a supervised training dataset associated with a software engineering task thereby generating a tool to perform the software engineering task.
    Type: Grant
    Filed: June 30, 2020
    Date of Patent: December 6, 2022
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
    Inventors: Colin Bruce Clement, Dawn Drain, Neelakantan Sundaresan, Alexey Svyatkovskiy
  • Multi-lingual code generation with zero-shot inference
    Patent number: 11513774
    Abstract: A neural transformer model with attention is trained to predict candidates to complete a line of source code with a zero-inference capability. The model is trained on an unsupervised training dataset that includes features from source code written in multiple programming languages. The features include a file-level context and a local context, where the file-level context includes a global context, a class context, a function context, and/or a method context for each class, function and/or method of the source code programs used in the training dataset. The local context includes method bodies, function bodies, and/or stand-alone code of main method routines. From these features, the model is able to learn to predict an ordered sequence of code elements that complete a line of source code in a programming language seen and not seen during training.
    Type: Grant
    Filed: January 3, 2021
    Date of Patent: November 29, 2022
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC.
    Inventors: Colin Bruce Clement, Shuai Lu, Neelakantan Sundaresan, Alexey Svyatkovskiy, Duyu Tang
  • CODE COMPLETION WITH HOLES
    Publication number: 20220374208
    Abstract: A code completion tool uses a neural transformer model with attention to generate syntactically-correct candidates with holes to complete a partially-formed code snippet. The model is trained to predict the expansion of non-terminal symbols of the production rules of the underlying grammar of the code snippet without being constrained to a left-to-right expansion order. A hole is a non-terminal symbol of the grammar of a programming language that marks a position in a candidate where the code completion engine is not certain of the production rule that should be used to expand the non-terminal symbol. The hole allows the code completion engine to expand other non-terminal symbols in a candidate and allow the user to guide the expansion of the holes in a candidate.
    Type: Application
    Filed: May 15, 2021
    Publication date: November 24, 2022
    Inventors: MILTIADIS ALLAMANIS, DAYA GUO, SHAO KUN DENG, NEELAKANTAN SUNDARESAN, ALEXEY SVYATKOVSKIY
  • Searchable texture index
    Patent number: 11494823
    Abstract: Electronic content that has a tactile dimension when presented on a tactile-enabled computing device may be referred to as tactile-enabled content. A tactile-enabled device is a device that is capable of presenting tactile-enabled content in a manner that permits a user to experience tactile quality of electronic content. In one example embodiment, a system is provided for generating content that has a tactile dimension when presented on a tactile-enabled device.
    Type: Grant
    Filed: January 21, 2021
    Date of Patent: November 8, 2022
    Assignee: eBay Inc.
    Inventors: Neelakantan Sundaresan, Anurag Bhardwaj, Robinson Piramuthu
  • DETECTION OF RUNTIME ERRORS USING MACHINE LEARNING
    Publication number: 20220342800
    Abstract: Runtime errors in a source code program are detected in advance of execution by machine learning models. Features representing a context of a runtime error are extracted from source code programs to train a machine learning model, such as a random forest classifier, to predict the likelihood that a code snippet has a particular type of runtime error. The features are extracted from a syntax-type tree representation of each method in a program. A model is generated for distinct runtime errors, such as arithmetic overflow, and conditionally uninitialized variables.
    Type: Application
    Filed: July 4, 2022
    Publication date: October 27, 2022
    Inventors: SHAUN MILLER, KALPATHY SITARAMAN SIVARAMAN, NEELAKANTAN SUNDARESAN, YIJIN WEI, ROSHANAK ZILOUCHIAN MOGHADDAM
  • Recommendations based on branding
    Patent number: 11475501
    Abstract: A method and a system for providing recommendations based on branding are disclosed. In example embodiments, an index comprising predetermined brand relationships is maintained. Each predetermined brand relationship comprises a first brand, a second brand, and a recommendation score between the first brand and the second brand. A corpus containing a plurality of user queries is also maintained. A seed set of brands corresponding to a category in the index is expanded by accessing the corpus containing the plurality of user queries, evaluating user queries of the plurality of user queries that contain a disjunction of brand terms, and identifying a new brand to add to the seed set based on the evaluating.
    Type: Grant
    Filed: August 13, 2019
    Date of Patent: October 18, 2022
    Assignee: PayPal, Inc.
    Inventors: Nishith Parikh, Neelakantan Sundaresan
  • FREQUENT SOURCE CODE PATTERN MINING
    Publication number: 20220326918
    Abstract: A data mining technique is used to find large frequently-occurring source code patterns from methods/APIs that can be used in code development. Simplified trees that represent the syntactic structure and type and method usage of a source code fragment, such as a method, are mined to find closed and maximal frequent subtrees which represent the largest frequently-occurring source code patterns or idioms associated with a particular type and method usage. These idioms are then used in an idiom web service and/or a code completion system to assist users in the development of source code programs.
    Type: Application
    Filed: June 28, 2022
    Publication date: October 13, 2022
    Inventors: CHRISTIAN ALMA BIRD, SHENGYU FU, NEELAKANTAN SUNDARESAN, NINA WANG, SHUO ZHANG
  • SEMI-SUPERVISED TRANSLATION OF SOURCE CODE PROGRAMS USING NEURAL TRANSFORMERS
    Publication number: 20220308848
    Abstract: An automated system for translating source code written in one programming language into a different programming language utilizes a neural transformer with attention trained on semi-supervised data. The model is jointly pre-trained with a masked language model objective and an autoregressive objective on a large unsupervised source code corpus to learn to comprehend the syntactic structure and semantics of source code. The pre-trained model is then fine-tuned with a token-type prediction objective and an autoregressive objective on supervised translation tasks and data augmented tasks to learn to translate source code from one programming language into a different programming language.
    Type: Application
    Filed: March 25, 2021
    Publication date: September 29, 2022
    Inventors: COLIN BRUCE CLEMENT, DAWN DRAIN, NEELAKANTAN SUNDARESAN, ALEXEY SVYATKOVSKIY, CHEN WU
  • Community based network shopping
    Patent number: 11455677
    Abstract: A system receives item data corresponding to an item list from a user. The item list may include one or more items. The system communicates the item list to a community group associated with the user and the system then receives member data from one or more members of the community group, wherein the member data is associated with the one or more items on the item list.
    Type: Grant
    Filed: October 16, 2020
    Date of Patent: September 27, 2022
    Assignee: eBay Inc.
    Inventor: Neelakantan Sundaresan
  • Systems and methods for saving and presenting a state of a communication session
    Patent number: 11455348
    Abstract: A system comprising a computer-readable storage medium storing at least one program, and a computer-implemented method for saving and presenting a state of a communication session are presented. The communication session may be established between a client device and an application server of a content publisher, and may include the presentation of content on the client device. In some embodiments, the method may include receiving user input to save a state of the communication session, and in response, temporarily storing session data representative of the state of the communication session for a predetermined duration of the communication session. The method may further include generating and presenting an interface that includes a visual representation of the session data, and allows a user to return to the saved state of the communication session.
    Type: Grant
    Filed: February 17, 2020
    Date of Patent: September 27, 2022
    Assignee: eBay Inc.
    Inventors: Esmeralda Carrillo, Kristy Brambila, Cassandra Gordon, Enrica Montilla Beltran, Neelakantan Sundaresan
  • Social sharing system
    Patent number: 11444991
    Abstract: A system, computer-readable storage medium storing at least one program, and computer-implemented method for providing recommendations based on social network sharing activity. Sharing activity relating to the sharing of the content item on a social network by a first user is accessed. Consumption information related to the consumption of the content item. A correlation between the sharing activity and the consumption information is determined. A recommendation is then generated based on the correlation.
    Type: Grant
    Filed: August 3, 2020
    Date of Patent: September 13, 2022
    Assignee: PayPal, Inc.
    Inventors: Neelakantan Sundaresan, Atish Das Sarma, Si Si, Elizabeth Churchill
  • Command-line script generation with relevance search
    Patent number: 11436236
    Abstract: A term-weighting and document-scoring function is used to search for a command line interface (CLI) script that is likely relevant to an operation specified in a natural language query. CLI scripts are created to perform various operations of a CLI-based application. A CLI script is associated with a description document having keywords associated with the individual commands used in the CLI script. The relevance of a CLI script to an intended operation is based on the term-weighting and document-scoring function which is applied to each component of each command in a CLI script and weighted accordingly.
    Type: Grant
    Filed: May 1, 2020
    Date of Patent: September 6, 2022
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
    Inventors: Spandan Garg, Yevhen Mohylevskyy, Jason R. Shaver, Neelakantan Sundaresan, Roshanak Zilouchian Moghaddam
  • NEURAL COMMAND LINE INTERFACE EXAMPLE GENERATION
    Publication number: 20220253712
    Abstract: An example generator tool generates an example illustrating correct usage of a command of a command line interface. A command may include a command name, zero or more subcommands, and one or more parameters with a corresponding parameter value. A template containing the correct syntax of the command is obtained from a template database. Parameter values for the template are generated from a neural transformer with attention given the command template.
    Type: Application
    Filed: April 19, 2021
    Publication date: August 11, 2022
    Inventors: COLIN BRUCE CLEMENT, ROSHANAK ZILOUCHIAN MOGHADDAM, NEELAKANTAN SUNDARESAN