Microsoft Technology Licensing, LLC

Apple Inc.

Vishwas Kulkarni

Timothy S Paek

Moises Goldszmidt

Juan Carlos Garcia

Anatoly D Adamov

Julia R Reisler

Yu-Chung Hsiao

Pavan Chitta

Amish Patel

Asela J Gunawardana

Jason Anthony Grieves

Dmytro Rudchenko

Daniel Edward Ostrowski

Asela Jeevaka Ranaweera Gunawardana

Johnson T Apacible

Bongshin Lee

Hong Z Tan

David Lee Nelson

Devlin David Bentley

Dmitry Rudchenko

Systems and methods are disclosed for triggering an update to a machine-learning model upon detecting that a distribution of particular (e.g., recently collected) input data set is sufficiently different from a distribution training input data set used to train the model. The distributions may be determined to be sufficiently different when a classifier can identify to which distribution individual data elements belong (e.g., to at least a predetermined degree). An update to the machine-learning model can include morphing weights used by the model and/or retraining the model.

Automated input-data monitoring to dynamically adapt machine-learning techniques

Embodiments are disclosed for a method of providing a user interface on a computing device. The method includes presenting a virtual keyboard on a display of the computing device, detecting input to the virtual keyboard. The method further includes, for each detected input, determining whether the input selects any of one or more delimiter keys, displaying a placeholder for the input responsive to the input not selecting any of the one or more delimiter keys, and receiving suggested candidate text from a word-level recognizer and replacing all currently displayed placeholders with the suggested candidate text responsive to the input selecting any of the one or more delimiter keys.

Display-efficient text entry and editing

An electronic device includes a display including a touch sensor, a contextual sensor configured to provide data indicative of an operating condition of the electronic device, one or more memories in which touch input instructions, touch event mapping instructions, and a touch event mapping model are stored, and a processor coupled to the memory. The processor is configured through execution of the touch input instructions to obtain data indicative of an initial assessment of touch event position via the touch sensor. The touch event mapping model maps the initial assessment of touch event position to an adjusted touch event position as a function of the data indicative of the operating condition of the electronic device. The processor is further configured through execution of the touch event mapping instructions to determine the adjusted touch event position based on the touch event mapping model, the data indicative of the initial assessment of touch event position, and the data indicative of the operating condition.

Model-based touch event location adjustment

Various technologies pertaining to provision of haptic feedback to users of computing devices with touch-sensitive displays are described. First haptic feedback is provided to assist a user in localizing a finger or thumb relative to a graphical object displayed on a touch-sensitive display, where no input data is provided to an application corresponding to the graphical object. A toggle command set forth by the user is subsequently identified; thereafter, an input gesture is received on the touch-sensitive display, and second haptic feedback is provided to aid the user in setting forth input data to the application.

Provision of haptic feedback for localization and data input

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Woodinville, WA, United States of America

Vishwas Kulkarni