Microsoft Technology Licensing, LLC

Amazon Technologies, Inc.

Xin Yang

Wenqing Jiang

Jason Thorpe

Shujuan Huang

Alperen Kok

Jacob Sean Lariviere

Stephen Bruce Broschart

Shiqi Wen

An autonomous mobile device (AMD) interacts with a user to provide tasks such as conveniently displaying information on a screen and moving with the user as they move. The AMD determines an area, or bounding box, of a user appearing within images obtained by a camera that is mounted on the AMD. A preferred area, with respect to the images, such as a center of the image, is specified to provide desired framing of images. As images are acquired by the camera, a difference between the bounding box and the preferred area is determined. Based at least in part on this difference, instructions are determined to move one or more of the cameras or the entire AMD to try and reframe the bounding box in subsequent images closer to the preferred area. Other factors, such as the user being backlit, may also be considered in determining the instructions.

System for autonomous mobile device motion control using image data

According to examples, an apparatus may include a processor and a memory on which is stored machine readable instructions that may cause the processor to generate a matrix based on features of reference entities and a respective allocation of value provided to each reference entity, apply first-stage machine-learning on the matrix to identify relevant features of the reference entities that correlate with the respective allocation of value provided to each reference entity, and access an identity of a target entity and target features of the target entity. The instructions may further cause the processor to apply second-stage machine-learning to generate a cluster comprising the target entity and a set of the reference entities based on the relevant features and determine a distribution of values allocated to the set. The distribution of values may be used to generate or assess a target allocation of value for the target entity.

Machine-learning for combinatorial decisioning

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Bellevue, WA, United States of America

Xin Yang