Microsoft Technology Licensing, LLC

Other

Lucas Bordeaux

Andrew Donald Gordon

Youssef Hamadi

Panos Periorellis

Shahram Izadi

Jamie Daniel Joseph Shotton

Andrew William Fitzgibbon

Pushmeet Kohli

Andrew Blake

Vishwa Vinay

John Michael Winn

Carsten Rother

Thomas Joseph Cashman

Thore Graepel

Jeremiah Spradlin

Filip Andrzej Radlinski

Federica Bogo

Thore Kurt Hartwig Graepel

Yoram Bachrach

Sameer Singh

Christian Kratzsch

Adi Ionel Botea

Checking and/or completing for data grids is described such as for grids having rows and columns of cells at least some of which contain data values such as numbers or categories. In various embodiments predictive probability distributions are obtained from an inference engine for one or more of the cells and the predictive probability distributions are used for various tasks such as to suggest values to complete blank cells, highlight cells having outlying values, identify potential errors, suggest corrections to potential errors, identify similarities between cells, identify differences between cells, cluster rows of the data grid, and other tasks. In various embodiments a graphical user interface displays a data grid and provides facilities for completing, error checking/correcting, and analyzing data in the data grid.

Checking and/or completion for data grids

New methods of relational database management are described, for example, to enable completion and checking of data in relational databases, including completion of missing foreign key values, to facilitate understanding of data in relational databases, to highlight data that it would be useful to add to a relational database and for other applications. In various embodiments, the schema of a relational database is used to automatically create a probabilistic graphical model that has a structure related to the schema. For example, nodes representing individual rows are linked to rows of other tables according to the database schema. In examples, data in the relational database is used to carry out inference using inference algorithms derived from the probabilistic graphical model. In various examples, inference results, comprising probability distributions each for an individual table cell, are used to fill missing data, highlight errors, and for other purposes.

Relational database management

A ground truth engine is described which has a memory holding a plurality of captured images depicting an articulated item. A processor of the engine is configured to access a parameterized, three dimensional (3D) model of the item. An optimizer of the ground truth engine is configured to compute ground truth values of the parameters of the 3D model for individual ones of the captured images, such that the articulated item depicted in the captured image fits the 3D model, the optimizer configured to take into account feedback data from one or more humans, about accuracy of a plurality of the computed values of the parameters.

Human feedback in 3D model fitting

A method is provided herein for managing a plurality of computing entities. The method includes sending a dynamic attribute dependency to one or more of the computing entities. The dynamic attribute dependency specifies a constraint for performing the management operation based on a dynamic attribute of each of the one or more computing entities. Additionally, the method includes scheduling, based on the plan, an atomic task configured to perform the management operation on each of the one or more a computing entities based on whether the constraint is resolved. The method further includes performing the atomic task if the constraint is resolved.

Dynamic attribute resolution for orchestrated management

Managing groups of entities is described. In an embodiment an administrator manages operations on a plurality of entities by constructing a management scenario which defines tasks to be applied on a group of entities. In an example the management scenario includes information on dependencies between entities and information on entity attributes, for example operating system version or CPU usage. In an embodiment an entity management engine converts the tasks and dependencies in the scenario to a management plan. In an example the management plan is a list of operations and conditions to be respected in applying an operation to an entity. In an embodiment the plan can be validated to ensure there are no conflicts. In an embodiment the entity management engine also comprises a scheduler which runs tasks contained in the plan and monitors their outcome.

Managing groups of computing entities

An outgoing message monitor is provided. In an embodiment, outgoing messages are monitored to detect potential errors and alerts may be triggered. Using information about a message such as an email, a first classifier classifies the email into an expected class and a second classifier classifies the email into an actual class. On the basis of a comparison of the expected and actual classes an alert may be triggered. In an embodiment, the second classifier uses information derived from text content of the email which may optionally be pre-processed. The first classifier, for example, uses other information about the email such as its intended recipients, information about the presence of attachments, information about whether the email is part of a thread and other information.

Outgoing message monitor

It is required to provide an automated process for forming a visually appealing digital collage (also referred to as a tapestry or photomontage) from a plurality of input images. Input images and a collage are labeled. Labels in the collage specify which regions of the input images are used to form those collage regions. An energy function is created for the labeling which contains terms that take into account various criteria to produce a collage. For example, those criteria may relate to the amount of information in the images, similarity of the images, entropy in the images or object class information. A multi-stage optimization process is applied to the energy function which is fast and enables large numbers of input images to be used to produce a collage.

Auto collage

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Cambridge, United Kingdom

Lucas Bordeaux