Microsoft Technology Licensing, LLC

Johnny S Campbell

Robert G Hawking

Christian Canton

Joseph John McDaid

Christopher John Gross

Benjamin Edward Rampson

Samuel C Radakovitz

Daniel C Battagin

Joseph M Chirilov

Claudio Vittorio Russo

Rishabh Tandon

David Mowatt

Eran Megiddo

Allan Folting

Michael J Smith

Rolando Jimenez Salgado

Muiris Woulfe

Stephen O'Driscoll

Venkat Pradeep Chilakamarri

Andreas Balzer

Konrad Tupaj

Marc Manuel Johannes Brockschmidt

Jenefer Lea Monroe

Safiya Bhojawala

Amarinder Singh Grewal

Sjoerd Roelof De Jong

Robert David Ohn Tinn

Juliana Patricia Vicente Franco

Sneha Khullar

Andrew William Stegmaier

Vikas Yadav

Carlos Augusto Otero

Andrew Donald Gordon

Lawrence Fubini Waldman

Benjamin C Chamberlain

Shahar Prish

Amy Lin

Brian L Welcker

Matthew Hart Fichtner

Andrew James Becker

Aaron Lamar Wilson

Liviu Asnash

Advait Sarkar

Dhirendra Kumar Bhupati

Ira Levin

Alexander Martynov

Michael Hopkins Smith

Prashant Anand Shirolkar

Neil Toronto

Robert Archer

Tom Hoke

Harrison Gordon

Anusha Iyer

Michael H Smith

Robert L Archer

Described herein is a software update distribution service that leverages reinforcement learning—a specific type machine learning algorithm—to discover or learn optimal times (e.g., a schedule) to download software updates and to install software updates for software applications installed on a group of client computing devices of a specific enterprise, in order to achieve one of several predefined goals or objectives selected for the specific enterprise, or for the specific group of client computing devices. Using reinforcement learning, a software-based agent learns to perform activities relating to software updates at specific times that minimize a penalty, wherein the penalty is derived based on a weighted combination of metrics, some of which relate to the impact of software update timing on network traffic and power consumption.

Reinforcement learning for controlling software update timing

Aspects disclosed herein relate to the use of navigational control UI elements to aid in navigating large surfaces on a touchscreen device. The navigational control UI element may be operable to facilitate traversal of the navigable surface along the axis upon which the navigational control UI element is placed. In alternate examples, the navigational control element may be operable to provide functionality to traverse or adjust the navigable surface along both the horizontal vertical axes. In still further aspects, other types of navigational control UI elements may provide the ability to directly jump to a specific position on the navigable surface.

Navigating long distances on navigable surfaces

Examples discussed herein relate to automatically creating lambda functions in spreadsheet applications, e.g., Microsoft Excel&#xae;. In an implementation, a method of automatically creating lambda functions in spreadsheet applications using a lambda shorthand notation is disclosed. The method includes analyzing contents of a cell of a spreadsheet to identify a formulaic expression and determining that the formulaic expression can define a body of a lambda function without using explicit lambda function notation or parameter declarations. The method further includes automatically creating and invoking the lambda function responsive to the determination. As discussed herein, creating the lambda function includes registering the lambda function in a lambda registry using the formulaic expression as the body of the lambda function that evaluates into an output value.

Automatically creating lambda functions in spreadsheet applications

Techniques for rendering shared data include receiving, from a data store by a computing device, data indicative of a persistent data object. The persistent data object is associated with a class indicative of a data type for information contained in the persistent data object. The persistent data object is operable to be inserted in a file generated by an application executing on the computing device. The visualization logic associated with the class may be received by the computing device. The information in the persistent data object is rendered using the selected method of visualization, and other information in the document is rendered using native rendering capabilities of the application.

Visualization platform for reusable data chunks

Systems, methods, and software are disclosed herein for enhancing functions and formulas in spreadsheets. A computing apparatus detects a beginning of a formula in a cell of a spreadsheet. In response to detecting the beginning of the formula, the computing apparatus identifies one or more vector representations of a context of the cell and supplies the one or more vector representations as input to one or more machine learning models. The one or more machine learning models produce output comprising one or more suggested functions for the formula and one or more suggested operands, which the computing apparatus presents in a user interface to the spreadsheet.

Suggested functions for formulas in spreadsheets

Techniques for managing data include receiving, at a data store, a persistent data object generated by a source application, the object configured to be compatible with a plurality of applications and document types. The object is associated with a unique identifier. In response to a request for the object, the object is accessed based on its unique identifier and sent to a computing device executing a destination application. The object is incorporated by and is compatible with a destination document being edited by the destination application. An update to the object is received that is generated by a user application editing a user document. In response to receiving an indication that the object has been inserted in the destination document, the update is sent by the data store to the destination computing device and is usable to update the object as incorporated in the destination document.

Data re-use across documents

Systems, methods, and software are disclosed herein for enhancing functions and formulas in spreadsheets. A computing apparatus detects a beginning of a formula in a cell of a spreadsheet. In response to detecting the beginning of the formula, the computing apparatus identifies a vector representation of a context of the cell and supplies the vector representation as input to one or more machine learning models. The one or more machine learning models produce output comprising one or more suggested functions for the formula and one or more suggested operands, which the computing apparatus presents in a user interface to the spreadsheet.

Form-based formula editing in spreadsheets

Examples discussed herein relate to rending lambdas in spreadsheet application, e.g., Microsoft Excel&#xae;. In an implementation, a method of rendering lambdas in a spreadsheet application is disclosed. The method includes accessing a data object corresponding to the lambda function. The data object includes a listing of metadata associated with the lambda function and one or more items of the metadata identify rendering functionality for the lambda function. The method further includes creating a visual representation of the lambda function based, at least in part, on the rendering functionality for the lambda function, and rendering, in the cell of the spreadsheet on a display screen of the computing device, the visual representation of the lambda function.

Rendering lambda functions in spreadsheet applications

Technology is disclosed herein for handing approximate (or uncertain) values in spreadsheet applications. More specifically, the technology describes spreadsheet applications that support arrays or sets of approximate (or uncertain) values as native entities. An approximate (or uncertain) value may be the value of a cell of the spreadsheet that is resolvable by formula, charts and other functionalities. In some implementations, approximate values may include a range of data and a probability distribution that can be automatically created by the spreadsheet application, generated based on context, input by the user, etc. Because the approximate (or uncertain) value is natively available, it can be incorporated in a spreadsheet like other values. Additionally, the approximate (or uncertain) values can automatically propagate through a spreadsheet calculation to obtain a final approximate result. The techniques also describe various ways to represent uncertain values in cells and to visualize the probability distribution.

Natively handling approximate values in spreadsheet applications

In non-limiting examples of the present disclosure, systems, methods and devices for interacting with data in a productivity application are presented. A plurality of values associated with the productivity application may be analyzed to determine whether they include a value that can be added to a set comprising a plurality of values with a set data type upon which the productivity application can execute a plurality of set operations. An indication to add at least one of the analyzed values as a member of the set may be received. At least one of the analyzed values may be added as a member of the set. An indication to perform a set operation associated with the set may be received and performed, and the result of the performed set operation may be displayed on a productivity application user interface.

Identification of sets and manipulation of set data in productivity applications

Aspects of the present disclosure relate to systems and methods for automatically constructing a new formula based upon an existing formula. Various methods are employed to analyze an existing formula in order to determine an intent. Once the intent is determined, a new formula may be constructed that satisfies the intent of the existing formula. Further aspects relate to validating the new formula to ensure it produces the same result as the existing formula which it is intended to replace. Various user interface elements are also disclosed which may be employed to provide the newly constructed formulas to users of an application. The various aspects to disclosed herein may be performed by an application, such as a spreadsheet application, performed in real-time, or provided as a remote service.

Constructing new formulas through auto replacing functions

In non-limiting examples of the present disclosure, systems, methods and devices for interacting with lambda functions are presented. An indication to store a lambda function may be received. The lambda function may comprise: executable information that is specific to a first spreadsheet application instance, executable information that is generic to spreadsheet application instances, and metadata describing the functionality of the lambda function. The lambda function may be stored, and an indication to apply the stored lambda function to data in a separate spreadsheet application instance may be received. The stored lambda function may be provided to the separate spreadsheet application instance for execution.

Distribution of lambda functions

Suggestions are automatically displayed in response to an event. For example, suggestions may be automatically displayed in response to a receiving an indication from a user to enter content (e.g. receiving a selection of a content entry area). The suggestions may be displayed before a user enters any characters and before an input device is displayed and/or used (e.g. keyboard, Software Input Panel (SIP), and the like. Suggestions may also be automatically displayed in response to detecting a pause while a user is entering content. For example, when a user is actively entering content, suggestions are not automatically displayed but when a user pauses a predetermined amount while entering content, suggestions are automatically displayed. The suggestions may be determined from content that may be seen on a display and/or hidden from view (e.g. hidden rows in a spreadsheet).

Automatically displaying suggestions for entry

Slicers are configured to filter tabular data arranged in columns. A user may use the slicers to filter tabular data from a client application and/or a server based application/service. Slicers may be created for one or more columns and for all/portion of the tabular data within a column. Selection of a slicer element filters the associated tabular data and updates a display of the other slicers. Interaction with the slicers may also update other user interface controls that filter the tabular data (e.g. selecting a slicer element changes a value of a filtering setting in a drop down menu and/or selecting the filtering setting in the drop down menu changes a state of a slicer element). A slicer element may be associated with other objects in the spreadsheet and/or included within one or more functions of a spreadsheet.

Slicer elements for filtering tabular data

Growing community of inventors

Woodinville, WA, United States of America

Johnny S Campbell