Abstract: Examples that relate to virtual controls in a mixed reality experience are described. One example provides a method comprising, via a mixed reality display device, displaying mixed reality content including a representation of a virtual control, and receiving sensor data indicating motion of a user digit. The method further comprises, based at least in part on the sensor data, determining a velocity of the user digit, and responsive to determining that the velocity of the user digit relative to a surface corresponding to the virtual control satisfies a velocity-based selection condition, triggering the virtual control.

Abstract: Techniques are described herein that are capable of adjusting a center frequency of an adaptive voltage controlled oscillator (VCO) that is included in an adaptive phase lock loop (PLL) and/or a phase difference target of the adaptive PLL. An adaptive PLL is a PLL that includes an adaptive VCO. An adaptive VCO is a VCO that is capable of adjusting its center frequency and/or a phase difference target of the adaptive PLL that includes the adaptive VCO. The adaptive PLL may be configured to drive (e.g., control) a device. A drive signal that is used to drive the device and a resulting output signal that is proportional to movement of the device may be fed back to respective inputs of the adaptive PLL so that the phases of those signals may be processed to facilitate adjustment of the center frequency and/or the phase difference target.

Abstract: Some storage systems are configured with VDL (valid data length) type controls that are implemented on a per cluster basis and, in some instances, on a sub-cluster basis, rather than simply a per file basis. In some instances, per-cluster VDL metadata for the storage clusters is stored and referenced at the edge data volume nodes of a distributed network for the storage system rather than, and/or without, storing or synchronizing the per-cluster VDL metadata at a master node that manages the corresponding storage clusters for the different data volume nodes. Sequence controls are also provided and managed by the master node and synchronized with the edge data volume nodes to further control access to data contained in the storage clusters.

Abstract: Examples discussed herein relate to automatically creating lambda functions in spreadsheet applications, e.g., Microsoft Excel®. 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.

Abstract: The present disclosure provides an experimentation framework for a computational environment in a distributed system. A machine-learning model may be created that predicts at least one output produced by the computational environment based on at least one input provided to the computational environment. During an evaluation time period that is subsequent to at least one modification being made to the computational environment, at least one modified output produced by the computational environment may be determined. The machine-learning model may be used to calculate at least one predicted output that would have been produced by the computational environment during the evaluation time period if the at least one modification had not been made. A determination may also be made about how the at least one modification affected the computational environment based on a comparison of the at least one modified output and the at least one predicted output.

Abstract: Examples of the present disclosure describe systems and methods of providing a people relevance platform. In aspects, an event may be generated by an application/service on a client device. The event may be transmitted to a people relevance platform. The people relevance platform may use the event to query one or more data sources for user contacts associated with the user. The people relevance platform may generate/modify a graph or model using the user contact data, and may provide the user contact data to the client device. The client device may update a local cache and provide the user contact data to the originating application. The client device may monitor the user selection of a contact, and transmit the selection information to the people relevance platform. The people relevance platform may modify the graph and/or model based on the selection information.

Abstract: While connected to cloud storage, a computing device writes data and metadata to the cloud storage, indicates success of the write to an application of the computing device, and, after indicating success to the application, writes the data and metadata to local storage of the computing device. The data and metadata may be written to different areas of the local storage. The computing device may also determine that it has recovered from a crash or has connected to the cloud storage after operating disconnected and reconcile the local storage with the cloud storage. The reconciliation may be based at least on a comparison of the metadata stored in the area of the local storage with metadata received from the cloud storage. The cloud storage may store each item of data contiguously with its metadata as an expanded block.

Abstract: Systems and techniques for a transfer model learning for relevance models are described herein. In an example, a system for member relevance prediction is adapted to collect a first data set of member interactions with the online service that occur on a first platform and train a first model using the first data set. The system for member relevance prediction may collect a second data set of member interactions with the online service that occur on a second platform. The system for member relevance prediction may predict a third data set related to member interactions using the first model and aggregate the first data set, the second data set, and the third data set. The system for member relevance prediction may train a second model for the second platform using the aggregated platform data and predict for the second platform, using the second model, online service items for the member.

Abstract: Database objects are retrieved from a database and parsed into normalized cached data objects. The database objects are stored in the normalized cached data objects in a cache store, and tenant data requests are serviced from the normalized cached data objects. The normalized cached data objects include references to shared objects in a shared object pool that can be shared across different rows of the normalized cached data objects and across different tenant cache systems.

Abstract: Methods for one click monitors in impact time detection for noise reduction in at-scale monitoring are performed by systems and devices. The methods automatically configure time window sizes and numbers of consecutive time windows for optimally detecting system alerts in at-scale systems and per dimension combinations, including updating settings over time to adapt to changing system behaviors. The past behavior of system performance metrics are analyzed to match configuration options and determine a best fitting or optimal combination of a highest detection accuracy in lowest time to detect for alerting. Optimal monitoring configurations are determined for each of up to hundreds of thousands of the metric dimensions across the system, and an end user is enabled to apply the determined, optimal configurations for system monitoring with a single selection.

Abstract: Techniques disclosed herein enable a system to reduce user authentication requirements during a user's travels by analyzing transportation data and/or event data sent to the user via a communication service, e.g. email. The system may analyze the data in order to determine where the user will be at some future time and, ultimately, to then validate access requests against such determinations to mitigate the need for heightened user authentication requirements while the user is traveling. For instance, the system may identify an airline reservation sent to the user and enable the user to confirm that she has corresponding travel plans. Once she confirms her travel plans, the system may refrain from increasing authentication requirements from Single-Factor Authentication (SFA) to Multi-Factor Authentication (MFA) input requirements for access requests that match the confirmed travel plans.

Abstract: Identifying data quality along a data flow. A method includes identifying quality metadata for two or more datasets. The quality metadata defines one or more of quality of a data source, accuracy of a dataset, completeness of a dataset, freshness of a dataset, or relevance of a dataset. At least some of the metadata is based on results of operations along a data flow. Based on the metadata, the method includes creating one or more quality indexes for the datasets. The one or more quality indexes include a characterization of quality of two or more datasets.

Abstract: The description relates to cameras and privacy covers for the cameras. One example can include a body defining a front-end and an opposing back-end that have matching profiles and a lens positioned in the front-end. This example can include an automatically self-aligning and self-retaining opaque privacy cover having a profile that matches both the front-end profile and the back-end profile of the body.

Abstract: Methods, systems, and computer storage media for providing action-recommendations (e.g., save action, collaboration action, and upload action) using cloud system operations in a cloud system. For example, action-recommendations are predicted using usage data of applications and communicated to a user (e.g., via a prompt) such that the user elects to perform or not perform the action-recommendation. In operation, usage data for an application and an action-recommendation profile are accessed. Determining that an action-recommendation should be generated is based on the usage data and the action-recommendation profile. The determination is further based on action scores and thresholds (e.g., save action, collaboration action, upload action). When the action scores meet certain thresholds, the action-recommendation is generated as a save-action-recommendation, a collaboration-action-recommendation, or an upload-action-recommendation.

Abstract: Systems and methods for providing a machine learning-powered framework to transform overloaded text documents is provided. The system generates a plurality of candidate templates offline. During runtime, the system accesses a text document and analyzes the text document to identify segmentation data. The segmentation data can indicate a plurality of segments derived from the text document. The system then accesses a plurality of candidate templates, whereby each candidate template comprises a plurality of pages having a different background element that shares a common theme. The plurality of candidate templates are ranked based on at least the segmentation data. The network then generates multiple presentation pages for each of a predetermined number of top ranked candidate templates by incorporating each of the plurality of segments into a corresponding page of the plurality of pages for each of the top ranked candidate templates.

Abstract: The automated creation of a dataflow graph of a standing query. Once the standing query dataflow graph is created, events may be flowed into the dataflow graph to execute the standing query. In execution, a store query is accessed. The store query is structured in accordance with a store query language. A syntax graph (such as an abstract syntax tree) of the store query may then be generated. Then, using the syntax graph and a set of rules of the store query language, the dataflow graph is automatically generated. This significant speeds up and makes more easy and efficient the conversion of a store query into a standing query.

Abstract: This document relates to natural language processing using a framework such as a neural network. One example method involves obtaining a first document and a second document and propagating attention from the first document to the second document. The example method also involves producing contextualized semantic representations of individual words in the second document based at least on the propagating. The contextualized semantic representations can provide a basis for performing one or more natural language processing operations.

Abstract: The present disclosure provides a technical solution of highly empathetic TTS processing, which not only takes a semantic feature and a linguistic feature into consideration, but also assigns a sentence ID to each sentence in a training text to distinguish sentences in the training text. Such sentence IDs may be introduced as training features into a processing of training a machine learning model, so as to enable the machine learning model to learn a changing rule for the changing of acoustic codes of sentences with a context of sentence. A speech naturally changed in rhythm and tone may be output to make TTS more empathetic by performing TTS processing with the trained model. A highly empathetic audio book may be generated using the TTS processing provided herein, and an online system for generating a highly empathetic audio book may be established with the TTS processing as a core technology.

Abstract: One example provides a system for reading birefringent data. The system comprises one or more light sources, a first polarization state generator positioned to generate first polarized light from light of a first wavelength band output by the one or more light sources, a second polarization state generator positioned to generate second polarized light from light of a second wavelength band output by the one or light sources, an image sensor configured to acquire an image of the sample region via the first polarized light and the second polarized light, a polarization state analyzer disposed between the sample region and the image sensor, a first bandpass filter configured to pass light of the first wavelength band onto the image sensor, and a second bandpass filter configured to pass light of the second wavelength band onto the image sensor.

Abstract: A method to allocate memory, in response to application requests, for a compact data structure having location data and a trailer section is provided. The trailer section of the compact data structure is checked to determine an offset for listings and indices representing the location data. Upon determining the offset, the listings and indices are loaded into memory and responses to the application requests are generated by utilizing the listings and indices stored in the memory.