公开(公告)号：US20230029481A1

公开(公告)日：2023-02-02

申请号：US17963028

申请日：2022-10-10

Applicant: Microsoft Technology Licensing, LLC

Inventor： Jonathan Daniel KEECH ,  Kesavan SHANMUGAM ,  Simon CALVERT ,  Mark A. WILSON-THOMAS ,  Vivian Julia LIM

IPC: G06N20/20 ,  G06F8/33

Abstract: Providing custom machine learning models to client computer systems. Multiple machine learning models are accessed. Client-specific data for multiple client computer systems are also accessed. For each of at least some of the client computer systems, performing the following actions: First, using the corresponding client-specific data for the corresponding client computer system to determine which subset of the multiple machine learning models is applicable to the corresponding client computer system. The subset of the multiple machine learning models includes more than one of the multiple machine learning models. Then, aggregating the determined subset of the multiple machine learning models to generate an aggregated subset of machine learning models that is customized to the corresponding client computer system.

公开(公告)号：US20200175423A1

公开(公告)日：2020-06-04

申请号：US16205070

申请日：2018-11-29

Applicant: Microsoft Technology Licensing, LLC

Inventor： Jonathan Daniel KEECH ,  Kesavan SHANMUGAM ,  Simon CALVERT ,  Mark A. WILSON-THOMAS ,  Vivian Julia LIM

IPC: G06N20/20 ,  G06F8/33

Abstract: Providing custom machine learning models to client computer systems. Multiple machine learning models are accessed. Client-specific data for multiple client computer systems are also accessed. For each of at least some of the client computer systems, performing the following actions: First, using the corresponding client-specific data for the corresponding client computer system to determine which subset of the multiple machine learning models is applicable to the corresponding client computer system. The subset of the multiple machine learning models includes more than one of the multiple machine learning models. Then, aggregating the determined subset of the multiple machine learning models to generate an aggregated subset of machine learning models that is customized to the corresponding client computer system.

公开(公告)号：US20200334054A1

公开(公告)日：2020-10-22

申请号：US16592470

申请日：2019-10-03

Applicant: Microsoft Technology Licensing, LLC

Inventor： Sumit GULWANI ,  Arjun RADHAKRISHNA ,  Abhishek UDUPA ,  Gustavo ARAUJO SOARES ,  Vu Minh LE ,  Anders MILTNER ,  Mark A. WILSON-THOMAS

IPC: G06F9/451 ,  G06F8/33 ,  G06F8/40

Abstract: Automatically identifying context-specific repeated transformations (such as repeated edit tasks) that are based on observation of the developer drafting or modifying code. As the developer modifies the code, the code passes through a series of states, one after the other. The computing system observes the series of states of the code. It is based on this observation that the computing system identifies repeated transformations of the code for potentially offering to continue performing the repeated transformations for the user. This alleviates the developer from having to manually perform the remainder of the repeated transformations.

公开(公告)号：US20200159505A1

公开(公告)日：2020-05-21

申请号：US16195318

申请日：2018-11-19

Applicant: Microsoft Technology Licensing, LLC

Inventor： Srivatsn NARAYANAN ,  Kesavan SHANMUGAM ,  Mark A. WILSON-THOMAS ,  Vivian Julia LIM ,  Jonathan Daniel KEECH ,  Shengyu FU

IPC: G06F8/35 ,  G06N20/00

Abstract: Improving the results and process of machine learning service in computer program development. A client's codebase is accessed. A set of features are extracted from the client's codebase. One or more features from the set of features are then selected. Thereafter, at least one of the selected features is sent to a machine learning service that uses the received feature(s) to build custom model(s) for the client's computer system.