-
公开(公告)号：US20220084510A1
公开(公告)日：2022-03-17
申请号：US17021892
申请日：2020-09-15
Applicant: Microsoft Technology Licensing, LLC
Inventor： Baolin Peng , Chenguang Zhu , Chunyuan Li , Xiujun Li , Jinchao Li , Nanshan Zeng , Jianfeng Gao
Abstract: This document relates to machine learning. One example includes a method or technique that can be performed on a computing device. The method or technique can include obtaining a task-adapted generative model that has been tuned using one or more task-specific seed examples. The method or technique can also include inputting dialog acts into the task-adapted generative model and obtaining synthetic utterances that are output by the task-adapted generative model. The method or technique can also include populating a synthetic training corpus with synthetic training examples that include the synthetic utterances. The synthetic training corpus may be suitable for training a natural language understanding model.
-
公开(公告)号：US11875787B2
公开(公告)日：2024-01-16
申请号：US17963766
申请日：2022-10-11
Applicant: Microsoft Technology Licensing, LLC
Inventor： Baolin Peng , Chenguang Zhu , Chunyuan Li , Xiujun Li , Jinchao Li , Nanshan Zeng , Jianfeng Gao
CPC classification number: G10L15/18 , G10L15/083 , G10L15/22
Abstract: This document relates to machine learning. One example includes a method or technique that can be performed on a computing device. The method or technique can include obtaining a task-semantically-conditioned generative model that has been pretrained based at least on a first training data set having unlabeled training examples and semantically conditioned based at least on a second training data set having dialog act-labeled utterances. The method or technique can also include inputting dialog acts into the semantically-conditioned generative model and obtaining synthetic utterances that are output by the semantically-conditioned generative model. The method or technique can also include outputting the synthetic utterances.
-
公开(公告)号：US10579423B2
公开(公告)日：2020-03-03
申请号：US15943206
申请日：2018-04-02
Applicant: Microsoft Technology Licensing, LLC
Inventor： Jinchao Li , Yu Wang , Karan Srivastava , Jianfeng Gao , Prabhdeep Singh , Haiyuan Cao , Xinying Song , Hui Su , Jaideep Sarkar
Abstract: Generally discussed herein are devices, systems, and methods for scheduling tasks to be completed by resources. A method can include identifying features of the task, the features including a time-dependent feature and a time-independent feature, the time-dependent feature indicating a time the task is more likely to be successfully completed by the resource, converting the features to feature values based on a predefined mapping of features to feature values in a first memory device, determining, by a gradient boost tree model and based on a first current time and the feature values, a likelihood the resource will successfully complete the task, and scheduling the task to be performed by the resource based on the determined likelihood.
-
公开(公告)号：US12032627B2
公开(公告)日：2024-07-09
申请号：US17526806
申请日：2021-11-15
Applicant: Microsoft Technology Licensing, LLC
Inventor： Jinchao Li , Lars H. Liden , Baolin Peng , Thomas Park , Swadheen Kumar Shukla , Jianfeng Gao
Abstract: Systems and methods are provided for determining a response to a query in a dialog. An entity extractor extracts rules and conditions associated with the query and determines a particular task. The disclosed technology generates a transformer-based dialog embedding by pre-training a transformer using dialog corpora including a plurality of tasks. A task-specific classifier generates a first set of candidate responses based on rules and conditions associated with the task. The transformer-based dialog embedding generates a second set of candidate responses to the query. The classifier accommodates changes made to a task by an interactive dialog editor as machine teaching. A response generator generates a response based on the first and second sets of candidate responses using an optimization function. The disclosed technology leverages both a data-driven, generative model (a transformer) based on dialog corpora and a user-driven, task-specific rule-based classifier that accommodating updates in rules and conditions associated with a particular task.
-
公开(公告)号：US10768908B1
公开(公告)日：2020-09-08
申请号：US16285180
申请日：2019-02-25
Applicant: Microsoft Technology Licensing, LLC
Inventor： Yu Wang , Yu Hu , Haiyuan Cao , Hui Su , Jinchao Li , Xinying Song , Jianfeng Gao
IPC: G06F8/35 , G06F16/901 , G06F8/70
Abstract: A workflow engine tool is disclosed that enables scientists and engineers to programmatically author workflows (e.g., a directed acyclic graph, “DAG”) with nearly no overhead, using a simpler script that needs almost no modifications for portability among multiple different workflow engines. This permits users to focus on the business logic of the project, avoiding the distracting tedious overhead related to workflow management (such as uploading modules, drawing edges, setting parameters, and other tasks). The workflow engine tool provides an abstraction layer on top of workflow engines, introducing a binding function that converts a programming language function (e.g., a normal python function) into a workflow module definition. The workflow engine tool infers module instances and induces edge dependencies automatically by inferring from a programming language script to build a DAG.
-
Patent Agency Ranking
公开(公告)号：US11734066B2
公开(公告)日：2023-08-22
申请号：US16737474
申请日：2020-01-08
Applicant: Microsoft Technology Licensing, LLC
Inventor： Jinchao Li , Yu Wang , Karan Srivastava , Jianfeng Gao , Prabhdeep Singh , Haiyuan Cao , Xinying Song , Hui Su , Jaideep Sarkar
CPC classification number: G06F9/4887 , G06F9/4881 , G06F9/5005 , G06F18/21 , G06N20/00
Abstract: Generally discussed herein are devices, systems, and methods for scheduling tasks to be completed by resources. A method can include identifying features of the task, the features including a time-dependent feature and a time-independent feature, the time-dependent feature indicating a time the task is more likely to be successfully completed by the resource, converting the features to feature values based on a predefined mapping of features to feature values in a first memory device, determining, by a gradient boost tree model and based on a first current time and the feature values, a likelihood the resource will successfully complete the task, and scheduling the task to be performed by the resource based on the determined likelihood.
-
公开(公告)号：US11508360B2
公开(公告)日：2022-11-22
申请号：US17021892
申请日：2020-09-15
Applicant: Microsoft Technology Licensing, LLC
Inventor： Baolin Peng , Chenguang Zhu , Chunyuan Li , Xiujun Li , Jinchao Li , Nanshan Zeng , Jianfeng Gao
Abstract: This document relates to machine learning. One example includes a method or technique that can be performed on a computing device. The method or technique can include obtaining a task-adapted generative model that has been tuned using one or more task-specific seed examples. The method or technique can also include inputting dialog acts into the task-adapted generative model and obtaining synthetic utterances that are output by the task-adapted generative model. The method or technique can also include populating a synthetic training corpus with synthetic training examples that include the synthetic utterances. The synthetic training corpus may be suitable for training a natural language understanding model.
-
公开(公告)号：US11327726B2
公开(公告)日：2022-05-10
申请号：US16945321
申请日：2020-07-31
Applicant: Microsoft Technology Licensing, LLC
Inventor： Yu Wang , Yu Hu , Haiyuan Cao , Hui Su , Jinchao Li , Xinying Song , Jianfeng Gao
IPC: G06F8/35 , G06F16/901 , G06F8/70
Abstract: A workflow engine tool is disclosed that enables scientists and engineers to programmatically author workflows (e.g., a directed acyclic graph, “DAG”) with nearly no overhead, using a simpler script that needs almost no modifications for portability among multiple different workflow engines. This permits users to focus on the business logic of the project, avoiding the distracting tedious overhead related to workflow management (such as uploading modules, drawing edges, setting parameters, and other tasks). The workflow engine tool provides an abstraction layer on top of workflow engines, introducing a binding function that converts a programming language function (e.g., a normal python function) into a workflow module definition. The workflow engine tool infers module instances and induces edge dependencies automatically by inferring from a programming language script to build a DAG.
-
公开(公告)号：US20190340030A1
公开(公告)日：2019-11-07
申请号：US15972968
申请日：2018-05-07
Applicant: Microsoft Technology Licensing, LLC
Inventor： Xinying Song , Jaideep Sarkar , Karan Srivastava , Jianfeng Gao , Prabhdeep Singh , Hui Su , Jinchao Li , Andreea Bianca Spataru
Abstract: Generally discussed herein are devices, systems, and methods for task routing. A method can include receiving, from a resource, a request for a task, in response to receiving the request, determining whether to retrieve a new task of new tasks stored in a first queue or a backlog task of backlog tasks stored in a second queue based on a combined amount of backlog tasks and new tasks relative to a capacity of the resource or the resources, retrieving the new task or the backlog task from the determined first queue or second queue, respectively, based on the determination, and providing the retrieved task to the resource.
-
公开(公告)号：US20230076095A1
公开(公告)日：2023-03-09
申请号：US17963766
申请日：2022-10-11
Applicant: Microsoft Technology Licensing, LLC
Inventor： Baolin Peng , Chenguang Zhu , Chunyuan Li , Xiujun Li , Jinchao Li , Nanshan Zeng , Jianfeng Gao
Abstract: This document relates to machine learning. One example includes a method or technique that can be performed on a computing device. The method or technique can include obtaining a task-adapted generative model that has been tuned using one or more task-specific seed examples. The method or technique can also include inputting dialog acts into the task-adapted generative model and obtaining synthetic utterances that are output by the task-adapted generative model. The method or technique can also include populating a synthetic training corpus with synthetic training examples that include the synthetic utterances. The synthetic training corpus may be suitable for training a natural language understanding model.
-
-
-
-
-
-
-
-
-
Search Results
13
records
(took 0.019 seconds)
