Microsoft Technology Licensing, LLC

Siemens Medical Solutions USA, Inc.

Adobe, Inc.

Yao Lu

Jue Wang

Dharma Kiritkumar Shukla

Isabelle L Banville

Akash Jeevan Sagar

Srikanth Kandula

Aditya G Bhandarkar

Xue Bai

Mayank Mehta

David T Fong

Kumarswamy P Valegerepura

Eddie Fusaro

Mark Nathan Wain

Muralidhara Varma Chiluvuri

Gilles D Guenette

Ravi S Vedula

Lisa Fearn

Yoon Woo Jun

Xinran Fan

Anthony Sottile

Beibin Li

A method of updating a trained cardinality estimation model includes receiving a cardinality estimation model with cardinality labels and detecting a drift in underlying data or predicates of the cardinality estimation model. The type of the detected drift is determined and new test queries that mimic test queries for the detected drift are synthesized. A portion of the synthesized test queries is selected to reduce annotation cost and used to update the cardinality estimation model.

Adapting learned cardinality estimators to data and workload drifts

Transducer bracket marking

Touch screen with graphical user interface

Techniques involving flexible video object boundary tracking are described. One or more curves, such as Bezier curves, are received as drawn by a user on an initial frame of video to define a boundary of an object in the frame. The curves are then mapped to a subsequent or previous frame of the video where the object is included but has a new or changed boundary. A segmentation boundary is determined for the object in the subsequent frame and endpoints of segments of the curves are snapped to the segmentation boundary. Additionally, confidence values are determined for subregions of the frame that include portions of the curves. These confidence values are used to update control points on the curve segments to fit the curve segments to the new or changed boundary of the object in the frame.

Flexible video object boundary tracking

The present invention supports the design of a process using a drawing surface that specifies the process with underlying programmatic constructs. In response to a user's command, a construct corresponding to a shape is selected from a palette and inserted onto a design region that shows the specified process. The command is verified to be consistent with semantics of an associated process type. If so, a visual image of the specified process is updated. If not, an indicator is generated in a proximity of a relevant portion of the visual image in order to help the user resolve the inconsistency. The user is able to correct errors before generating computer-executable instructions from a high-level code emission. Computer-executable instructions are also generated from high-level code emission. A process engine is cognizant of the associated high-level lines of code and an infrastructure knowledge base while executing the computer-executable instructions.

Orchestration designer

Growing community of inventors

Seattle, WA, United States of America

Yao Lu