Patents by Inventor Eric P. Xing

Eric P. Xing 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: 11543830
    Abstract: An unsupervised real to virtual domain unification model for highway driving, or DU-drive, employs a conditional generative adversarial network to transform driving images in a real domain to their canonical representations in the virtual domain, from which vehicle control commands are predicted. In the case where there are multiple real datasets, a real-to-virtual generator may be independently trained for each real domain and a global predictor could be trained with data from multiple real domains. Qualitative experiment results show this model can effectively transform real images to the virtual domain while only keeping the minimal sufficient information, and quantitative results verify that such canonical representation can eliminate domain shift and boost the performance of control command prediction task.
    Type: Grant
    Filed: September 24, 2018
    Date of Patent: January 3, 2023
    Assignee: PETUUM, INC.
    Inventors: Xiaodan Liang, Eric P Xing
  • Publication number: 20210358588
    Abstract: A system for predicting medications to prescribe to a patient includes a text encoding module and a medication prediction module. The text encoding module is configured to obtain a clinical-information vector from clinical information of the patient. The medication prediction module configured to apply a machine-learned medication-prediction algorithm to the clinical-information vector to select a subset of medications to prescribe to the patient. The machine-learned medication-prediction algorithm is designed with a diversity-promoting regularization model, and is configured to simultaneously consider correlations among different medications and dependencies between patient information and medications when selecting a subset of medications to prescribe to the patient.
    Type: Application
    Filed: July 28, 2021
    Publication date: November 18, 2021
    Inventors: Pengtao Xie, Eric P. Xing
  • Publication number: 20210357816
    Abstract: A computer in a distributed computing system is disclosed. The computer includes: a graphics processing unit (GPU) memory; a central processing unit (CPU) memory comprising a Key-Value Store (KVS) module; an execution engine module configured to run a deep learning (DL) program to create a plurality of operator graph layers in the graphics processing unit memory; a client library module configured to create a GPU-CPU synchronization (GCS) module for each of the plurality of operator graph layers; a coordination service module configured to compute network cost of a first and a second communication scheme and select, based on the network cost, one of the first and second communication scheme for transmitting data associated with one of the plurality of operator graph layers from a corresponding GCS module.
    Type: Application
    Filed: July 28, 2021
    Publication date: November 18, 2021
    Inventors: Wei Dai, Hao Zhang, Eric P. Xing, Qirong Ho
  • Publication number: 20210335469
    Abstract: A system for assigning concepts to a medical image includes a visual feature module and a tagging module. The visual feature module is configured to obtain an image feature vector from the medical image. The tagging module is configured to apply a machine-learned algorithm to the image feature vector to assign a set of concepts to the image. The system may also include a text report generator that is configured to generate a written report describing the medical image based on the set of concepts assigned to the medical image.
    Type: Application
    Filed: July 2, 2021
    Publication date: October 28, 2021
    Applicant: Petuum, Inc.
    Inventors: Pengtao Xie, Eric P. Xing
  • Publication number: 20200379789
    Abstract: A system including a master machine and a plurality of worker machines is disclosed. the master machine includes, for example, an API server configured to receive a job description; a resource allocation module configured to determine a number of virtual machines required to perform a job based on the job description; a container scheduling module configured to create a container containing the number of virtual machines required to perform the job, wherein at least two of the virtual machines in the container resides on different worker machines, and wherein each of the virtual machines is configured to run a same application to perform the job.
    Type: Application
    Filed: August 19, 2020
    Publication date: December 3, 2020
    Inventors: Wei Dai, Weiren Yu, Eric P. Xing, Aurick Qiao, Qirong Ho
  • Patent number: 10782988
    Abstract: A system including a master machine and a plurality of worker machines is disclosed. The master machine includes, for example, an API server configured to receive a job description; a resource allocation module configured to determine a number of virtual machines required to perform a job based on the job description; a container scheduling module configured to create a container containing the number of virtual machines required to perform the job, wherein at least two of the virtual machines in the container resides on different worker machines, and wherein each of the virtual machines is configured to run a same application to perform the job.
    Type: Grant
    Filed: October 27, 2017
    Date of Patent: September 22, 2020
    Assignee: Petuum Inc.
    Inventors: Wei Dai, Weiren Yu, Eric P Xing, Aurick Qiao, Qirong Ho
  • Publication number: 20190171223
    Abstract: An unsupervised real to virtual domain unification model for highway driving, or DU-drive, employs a conditional generative adversarial network to transform driving images in a real domain to their canonical representations in the virtual domain, from which vehicle control commands are predicted. In the case where there are multiple real datasets, a real-to-virtual generator may be independently trained for each real domain and a global predictor could be trained with data from multiple real domains. Qualitative experiment results show this model can effectively transform real images to the virtual domain while only keeping the minimal sufficient information, and quantitative results verify that such canonical representation can eliminate domain shift and boost the performance of control command prediction task.
    Type: Application
    Filed: September 24, 2018
    Publication date: June 6, 2019
    Inventors: Xiaodan Liang, Eric P. Xing
  • Publication number: 20180307509
    Abstract: A system including a master machine and a plurality of worker machines is disclosed. The master machine includes, for example, an API server configured to receive a job description; a resource allocation module configured to determine a number of virtual machines required to perform a job based on the job description; a container scheduling module configured to create a container containing the number of virtual machines required to perform the job, wherein at least two of the virtual machines in the container resides on different worker machines, and wherein each of the virtual machines is configured to run a same application to perform the job.
    Type: Application
    Filed: October 27, 2017
    Publication date: October 25, 2018
    Inventors: Wei Dai, Weiren Yu, Eric P. Xing, Aurick Qiao, Qirong Ho
  • Publication number: 20140160132
    Abstract: A method performed by one or more processors, comprising: receiving genomic data and trait data representative of a plurality of traits of one or more individuals; determining a structure of one or more of the genomic data and the trait data; selecting, in response to the determined structure, a structured association algorithm for execution with the genomic data and the trait data; generating, based on execution of the selected, structured association algorithm against the genomic data and the trait data, structured association data indicative of associations among the genomic data and the trait data, wherein the associations are at least partly identified based on the structure; and generating data for a graphical user interface, that when rendered on a display device, comprises: a visual representation of at least a portion of the structured association data.
    Type: Application
    Filed: July 12, 2012
    Publication date: June 12, 2014
    Applicant: CARNEGIE MELLON UNIVERSITY
    Inventors: Eric P. Xing, Ross Eugene Curtis