公开(公告)号：US11379710B2

公开(公告)日：2022-07-05

申请号：US16805019

申请日：2020-02-28

Applicant: International Business Machines Corporation

Inventor： Dakuo Wang ,  Chuang Gan ,  Ming Tan ,  Arunima Chaudhary ,  Lin Ju

IPC: G06N3/04 ,  G06K9/62 ,  G06N3/08

Abstract: In accordance with an embodiment of the invention, a method is provided for personalizing machine learning models for users of an automated machine learning system, the machine learning models being generated by an automated machine learning system. The method includes obtaining a first set of datasets for training first, second, and third neural networks, inputting the training datasets to the neural networks, tuning hyperparameters for the first, second, and third neural networks for testing and training the neural networks, inputting a second set of datasets to the trained neural networks and the third neural network generating a third output data including a relevance score for each of the users for each of the machine learning models, and displaying a list of machine learning models associated with each of the users, with each of the machine learning models showing the relevance score.

公开(公告)号：US20220172038A1

公开(公告)日：2022-06-02

申请号：US17106966

申请日：2020-11-30

Applicant: International Business Machines Corporation

Inventor： Bei Chen ,  Dakuo Wang ,  Martin Wistuba ,  Beat Buesser ,  Long VU ,  Chuang Gan ,  Mathieu Sinn

IPC: G06N3/08 ,  G06N3/04

Abstract: A system and method for automatically generating deep neural network architectures for time series prediction. The system includes a processor for: receiving a prediction context associated with a current use case; based on the associated prediction context, selecting a prediction model network configured for a current use case time series prediction task; replicating the selected prediction model network to create a plurality of candidate prediction model networks; inputting a time series data to each of the plurality of the candidate prediction model network; train, in parallel, each respective candidate prediction model network of the plurality with the input time series data; modifying each of the plurality of the candidate prediction model network by applying a respective different set of one or more model parameters while being trained in parallel; and determine a fittest modified prediction model network for solving the current use case time series prediction task.

公开(公告)号：US20220113964A1

公开(公告)日：2022-04-14

申请号：US17069402

申请日：2020-10-13

Applicant: International Business Machines Corporation

Inventor： Dakuo Wang ,  Lingfei Wu ,  Yi Wang ,  Xuye Liu ,  Chuang Gan ,  Si Er Han ,  Bei Chen ,  Ji Hui Yang

IPC: G06F8/73 ,  G06N20/00 ,  G06F40/169

Abstract: One embodiment of the invention provides a method for automated code annotation in machine learning (ML) and data science. The method comprises receiving, as input, a section of executable code. The method further comprises classifying, via a ML model, the section of executable code with a stage classification label indicative of a stage within a workflow for automated ML that the executable code applies to. The method further comprises categorizing, based on the stage classification label, the section of executable code with a category of annotation that is most appropriate for the section of executable code. The method further comprises generating a suggested annotation for the section of executable code based on the category of annotation. The method further comprises providing, as output, the suggested annotation to a display of an electronic device for user review. The suggested annotation is user interactable via the electronic device.

公开(公告)号：US11288578B2

公开(公告)日：2022-03-29

申请号：US16597937

申请日：2019-10-10

Applicant: International Business Machines Corporation

Inventor： Dakuo Wang ,  Ming Tan ,  Mo Yu ,  Haoyu Wang ,  Yupeng Gao ,  Chuang Gan

IPC: G06N3/08 ,  G06N20/00 ,  H04L51/42 ,  H04L51/00 ,  G06N3/04

Abstract: A computer system identifies threads in a communication session. A feature vector is generated for a message in a communication session, wherein the feature vector includes elements for features and contextual information of the message. The message feature vector and feature vectors for a plurality of threads are processed using machine learning models each associated with a corresponding thread to determine a set of probability values for classifying the message into at least one thread, wherein the threads include one or more pre-existing threads and a new thread. A classification of the message into at least one of the threads is indicated based on the set of probability values. Classification of one or more prior messages is adjusted based on the message's classification. Embodiments of the present invention further include a method and program product for identifying threads in a communication session in substantially the same manner described above.

公开(公告)号：US20220036246A1

公开(公告)日：2022-02-03

申请号：US16942247

申请日：2020-07-29

Applicant: International Business Machines Corporation

Inventor： Bei Chen ,  Long VU ,  Syed Yousaf Shah ,  Xuan-Hong Dang ,  Peter Daniel Kirchner ,  Si Er Han ,  Ji Hui Yang ,  Jun Wang ,  Jing James Xu ,  Dakuo Wang ,  Dhavalkumar C. Patel ,  Gregory Bramble ,  Horst Cornelius Samulowitz ,  Saket Sathe ,  Chuang Gan

IPC: G06N20/20

Abstract: Techniques regarding one or more automated machine learning processes that analyze time series data are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise a time series analysis component that selects a machine learning pipeline for meta transfer learning on time series data by sequentially allocating subsets of training data from the time series data amongst a plurality of machine learning pipeline candidates.

公开(公告)号：US11238236B2

公开(公告)日：2022-02-01

申请号：US16595550

申请日：2019-10-08

Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION

Inventor： Dakuo Wang ,  Ming Tan ,  Chuang Gan ,  Haoyu Wang

IPC: G06F40/30 ,  H04L29/06 ,  G06N3/08 ,  G06N3/04 ,  H04L12/58

Abstract: Systems and methods provide for automated messaging summarization and ranking. The systems and methods may use an integrated machine learning model to perform thread detection, thread summarization, and summarization ranking. The messages may be received from a team chat application, organized, summarized and ranked by the machine learning model, and the results may be returned to the team chat application. In some cases, the ranking may be different for different users of the team chat application.

公开(公告)号：US11157554B2

公开(公告)日：2021-10-26

申请号：US16674402

申请日：2019-11-05

Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION

Inventor： Chuang Gan ,  Abhishek Bhandwaldar ,  Yang Zhang ,  Xiaoxiao Guo

IPC: G06F16/30 ,  G06F16/73 ,  G06N20/00 ,  G06F16/783 ,  G06F16/901 ,  G06F16/242

Abstract: A method, system, and program product for generating and modifying a video response is provided. The method includes receiving an audio/video file. Parsed video features of the audio/video file are generated with respect to a first graph. Parsed audio features of the audio/video file are generated with respect to a second graph. The first graph is placed overlaying the second graph and at least one intersection point between the first graph and the second graph is determined. A natural language query is executed with respect to the audio/video file and a parsed query entity is generated from the natural language query. The parsed query entity is analyzed with respect to the intersection point and a node of the intersection point comprising similar features is determined with respect to the parsed query entity. A resulting natural language response with respect to the natural language query is generated.

公开(公告)号：US11057330B2

公开(公告)日：2021-07-06

申请号：US16551321

申请日：2019-08-26

Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION

Inventor： Ming Tan ,  Haoyu Wang ,  Dakuo Wang ,  Chuang Gan

IPC: H04L12/58 ,  G06F40/30

Abstract: A deep learning module classifies messages received from a plurality of entities into one or more conversation threads. In response to receiving a subsequent message, the deep learning module determines which of the one or more conversation threads and a new conversation thread is contextually a best fit for the subsequent message. The subsequent message is added to the determined conversation thread.

公开(公告)号：US20210124987A1

公开(公告)日：2021-04-29

申请号：US16661501

申请日：2019-10-23

Applicant: International Business Machines Corporation

Inventor： Chuang Gan ,  Ming Tan ,  Yang Zhang ,  Dakuo Wang

IPC: G06K9/62 ,  G06K9/46 ,  G06N3/08

Abstract: Systems and techniques that facilitate few-shot temporal action localization based on graph convolutional networks are provided. In one or more embodiments, a graph component can generate a graph that models a support set of temporal action classifications. Nodes of the graph can correspond to respective temporal action classifications in the support set. Edges of the graph can correspond to similarities between the respective temporal action classifications. In various embodiments, a convolution component can perform a convolution on the graph, such that the nodes of the graph output respective matching scores indicating levels of match between the respective temporal action classifications and an action to be classified. In various embodiments, an instantiation component can input into the nodes respective input vectors based on a proposed feature vector representing the action to be classified. In various cases, the respective temporal action classifications can correspond to respective example feature vectors, and the respective input vectors can be concatenations of the respective example feature vectors and the proposed feature vector.

公开(公告)号：US20210103636A1

公开(公告)日：2021-04-08

申请号：US16595550

申请日：2019-10-08

Applicant: International Business Machines Corporation

Inventor： Dakuo Wang ,  Ming Tan ,  Chuang Gan ,  Haoyu Wang

IPC: G06F17/27 ,  H04L29/06 ,  H04L12/58 ,  G06N3/04 ,  G06N3/08

Abstract: Systems and methods provide for automated messaging summarization and ranking. The systems and methods may use an integrated machine learning model to perform thread detection, thread summarization, and summarization ranking. The messages may be received from a team chat application, organized, summarized and ranked by the machine learning model, and the results may be returned to the team chat application. In some cases, the ranking may be different for different users of the team chat application.