Abstract: Systems are provided for improving computer security systems that are based on user risk scores. These systems can be used to improve both the accuracy and usability of the user risk scores by applying multiple tiers of machine learning to different the user risk profile components used to generate the user risk scores and in such a manner as to dynamically generate and modify the corresponding user risk scores.

Abstract: Techniques for securing displayed data on computing devices are disclosed. One example technique includes upon determining that the computing device is unlocked, capturing and analyzing an image in a field of view of the camera of the computing device to determine whether the image includes a human face. In response to determining that the image includes a human face, the technique includes determining facial attributes of the human face in the image via facial recognition and whether the human face is that of an authorized user of the computing device. In response to determining that the human face is not one of an authorized user of the computing device, the technique includes converting user data on the computing device from an original language to a new language to output on a display of the computing device, thereby securing the displayed user data even when the computing device is unlocked.

Abstract: A method and system for predicting an intended time interval for a content segment may include receiving a request for natural language processing (NLP) of the content segment, the content segment including one or more temporal expressions, accessing contextual data associated with each of the one or more temporal expressions, decoding the content segment into a program that describes a temporal logic of the content segment based on the one or more temporal expressions, evaluating the program using the contextual data to predict an intended time interval for the content segment, and providing the intended time interval as an output.

Abstract: Techniques are described herein that are capable of evaluating a result of enforcement of access control policies instead of enforcing the access control policies. For instance, a result of enforcement of an access control policy with regard to sign-in processes is evaluated instead of enforcing the access control policy with regard to the sign-in processes. The evaluation includes monitoring access requests that are received during the sign-in processes. Each access request requests access to a resource. The evaluation further includes comparing attributes of each access request against the access control policy that specifies criteria that are to be satisfied as a prerequisite to granting access to the resource to which access is requested by the respective access request. Metadata associated with the sign-in processes is generated instead of enforcing the access control policy with regard to the sign-in processes.

Abstract: A method and system for providing one or more suggested application features to a user of an application may include receiving an indication of a user action in a document, accessing contextual document data associated with the document, providing at least one of information about the user action or the contextual document data as input to a machine-learning (ML) model to predict a desired intent for the document, obtaining the predicted desired intent as an output from the ML model, identifying based on the predicted desired intent one or more application features that fulfil the desired intent, and providing data about the one or more application features for display.

Abstract: Making an information retrieval process public, so that it can be followed by others, allows capturing of an interest graph that allows people to learn more about shared interests with other people. This also allows items of interest to a trusted resource (such as an expert) to be identified. These items can then be brought to the attention of other users that share the same interest as the expert. In addition, by keeping track of what particular content a user has already seen, the system can bring items of interest to the user's attention, where the user has not yet seen those items.

Abstract: A user interface may present multiple presentation slides for user selection. Each slide may include one or more shapes, and a shape thread may be associated with each shape on the slide. For a selected slide, the user interface may present one or more shape threads associated with the selected slide. Each shape displayed on the selected slide may be associated with a particular shape thread, and a user may independently adjust one or more slide transition attributes of a shape via the associated shape thread.

Abstract: A method for function call invocation is described. A function call that is implemented in a first programming language and corresponds to a function implemented in a second programming language is received by an application bridge interface implemented in the first programming language. The first programming language is different from the second programming language. A common data structure is generated by a bridge module based at least in part on the function call received by the application bridge interface. The common data structure is sent by the bridge module to a native bridge interface implemented in the second programming language. The common data structure is converted by the native bridge interface to a native data structure implemented in the second programming language. The function is called by the native bridge interface using the native data structure implemented in the second programming language.

Abstract: Techniques for mitigating loss of vaporized working fluid in a two-phase immersion cooling system may be implemented using one or more supplemental condensers that facilitate condensation of vaporized working fluid when the immersion tank is open, and one or more vapor collection points that are in fluid communication with at least one supplemental condenser. One or more fluid displacement devices may be configured to create suction pressure at the one or more vapor collection points. One or more vents may be positioned in the door. The one or more vents may be configured to permit movement of air from outside the immersion tank into an interior portion of the immersion tank without permitting loss of vaporized working fluid. A directional blowing device may be configured to blow a gaseous substance against a computing device in a downward direction as the computing device is being pulled upward out of the immersion tank.

Abstract: High surface area coatings are applied to solid substrates to increase the surface area available for solid-phase synthesis of polymers. The high surface area coatings use three-dimensional space to provide more area for functional groups to bind polymers than an untreated solid substrate. The polymers may be oligonucleotides, polypeptides, or another type of polymer. The solid substrate is a rigid supportive layer made from a material such as glass, a silicon material, a metal material, and plastic. The coating may be thin films, hydrogels, microparticles. The coating may be made from a metal oxide, a high-? dielectric, a low-? dielectric, an etched metal, a carbon material, or an organic polymer. The functional groups may be hydroxyl groups, amine groups, thiolate groups, alkenes, n-alkenes, alkalines, N-Hydroxysuccinimide (NHS)-activated esters, polyaniline, aminosilane groups, silanized oxides, oligothiophenes, and diazonium compounds.

Abstract: A function processing service may receive a request to execute source code. The source code may include instructions to perform a function. The function processing service may determine whether at least one hardware acceleration condition has been satisfied for the function. If at least one hardware acceleration condition has been satisfied, the instructions in the source code may be translated into hardware-specific code corresponding to a hardware circuit. The hardware circuit may be configured based on the hardware-specific code, and the hardware circuit may perform the function. The function processing service may then provide the result obtained from the hardware circuit to the requesting entity.

Abstract: Techniques of reproduction of graph data during query time are disclosed herein. One example technique includes receiving, at a query processor, a query having a set of predicates to be evaluated on data in a graph. Upon receiving the query, the example technique includes evaluating the set of predicates based on data in the first or second partition of the graph and recording a sequence of query states of the first or second partition whose data is used to evaluate each of the set of predicates. Subsequently, the example technique includes constructing a set of snapshots of the data in the first or second partition based on the recorded query states and reevaluating the set of predicates on the constructed set of snapshots of the data in the first or second partition to troubleshoot the detected query error when the set of predicates were previously evaluated.

Abstract: In an implementation, a computing device under the control of a spreadsheet application displays a spreadsheet in a user interface. The application detects a user action in the spreadsheet associated with an unstructured table and responsively drives the computer to display a suggestion component in the user interface. A selection of the component causes the computer to display a preview of a suggested table feature in the user interface.

Abstract: In non-limiting examples of the present disclosure, systems, methods and devices for executing gesture operations are provided. A touchpad gesture manager and a touchscreen gesture manager may be maintained. Both managers may comprise the identities of gesture operations and conditions for executing the gesture operations. The conditions for one or more touchscreen gesture operations may be the same as the conditions for one or more corresponding touchpad gesture operations. The gestures that have same conditions for the touchscreen and the touchpad may comprise application window operations and virtual desktop transition operations. In some examples, one or more display elements, animations, or intermediate operations may be different in executing the touchscreen operations than for executing the touchpad operations.

Abstract: A machine reading comprehension system (MRCS) can analyze a larger-sized document that includes multiple pages to predict an answer to a query. For example, the document can have two, five, tens, or hundreds of pages. The MRCS divides the document into multiple sections with each section including a portion of the document. Each section is processed separately by one or more processing circuitries to determine a score for that section. The score indicates how related the section is to the query and/or a probability that the section provides a possible answer to the query. Once all of the sections have been analyzed, the sections are ranked by their scores and a subset of the ranked sections are processed again to determine a predicted answer to the query.

Abstract: A method may include accessing, from a data store, telemetry data for an application, the telemetry data identifying actions executed by the application for a set of users of the application; retrieving an engagement index for the application using the telemetry data based on an engagement index profile, the engagement index profile identifying a selection of actions and a set of calculation dimensions; and presenting a user interface, the user interface including: a first portion identifying the selection of actions; a second portion identifying the set of calculation dimensions; a third portion identifying an original value of an action of the selection of actions with respect to a dimension in the set of calculation dimensions; and a fourth portion identifying a weighted composite value of the action with respect to set of calculation dimensions.

Abstract: Some embodiments determine automatically which synthesized or otherwise autocreated suggestions for source code editing are presented to developers. Some filter out autocreated coding suggestions that have not been sufficiently endorsed by a developer's team, based on a suggestion trust score. The trust score may reflect the suggestion's adoption in a particular repository or codebase, or affiliation of the suggestion with a library release, or an actual or implied review of the suggestion by team members. Some suggestion filters enhance existing development team code review practices, by offering endorsed suggestions in autocompletion or analysis interfaces of tools and by withholding non-endorsed suggestions from display. Context illustrating the autocreated suggestion's provenance may be displayed to help developers decide whether to adopt the suggestion themselves while editing code.

Abstract: The present invention extends to methods, systems, and computer program products for identifying and consenting to permissions for workflow and code execution. Aspects of the invention can be used to automatically scan a workflow or code definition to identify (potentially all) the actions/triggers a workflow or program intends to perform on behalf of a user. The user is shown the actions/triggers the workflow or program intends to perform (e.g., at a user interface) before consent to perform the actions/triggers is granted. As such, a user is aware of intended actions/triggers of a workflow or program before granting consent. Further, since actions/triggers are identified from the workflow or code definition (and not formulated by an author), permission requests better align with permissions that workflow or program functionality actually uses during execution.

Abstract: The disclosure is directed towards controlling the persistency of information provided to a service worker. A method includes receiving a response that includes response data. The response is received at a security service and was transmitted by a second computing device in response to receiving an information request from a first computing device. The first computing device implements a service worker. Sensitive data included in the response data is identified. The response includes caching instructions that instruct the service worker to cache the sensitive data at the first computing device. In response to identifying the sensitive data, the caching instructions are updated such that any portion of the response data that the updated caching instructions instruct the service worker to cache at the first computing device excludes the sensitive data. The updated response is transmitted to the first computing device and includes the response data and the updated caching instructions.

Abstract: This application relates to video encoding and decoding, and specifically to tools and techniques for using and providing supplemental enhancement information in bitstreams. Among other things, the detailed description presents innovations for bitstreams having supplemental enhancement information (SEI). In particular embodiments, the SEI message includes picture source data (e.g., data indicating whether the associated picture is a progressive scan picture or an interlaced scan picture and/or data indicating whether the associated picture is a duplicate picture). The SEI message can also express a confidence level of the encoder's relative confidence in the accuracy of this picture source data. A decoder can use the confidence level indication to determine whether the decoder should separately identify the picture as progressive or interlaced and/or a duplicate picture or honor the picture source scanning information in the SEI as it is.

Abstract: Techniques and tools for encoding enhancement layer video with quantization that varies spatially and/or between color channels are presented, along with corresponding decoding techniques and tools. For example, an encoding tool determines whether quantization varies spatially over a picture, and the tool also determines whether quantization varies between color channels in the picture. The tool signals quantization parameters for macroblocks in the picture in an encoded bit stream. In some implementations, to signal the quantization parameters, the tool predicts the quantization parameters, and the quantization parameters are signaled with reference to the predicted quantization parameters. A decoding tool receives the encoded bit stream, predicts the quantization parameters, and uses the signaled information to determine the quantization parameters for the macroblocks of the enhancement layer video. The decoding tool performs inverse quantization that can vary spatially and/or between color channels.

Abstract: A cloud computing capacity management system can include a fine-grained admission control layer, a policy engine, and an enforcement layer. The fine-grained admission control layer can be configured to ingest capacity signals and create a capacity mitigation policy, based at least in part on the capacity signals, to protect available capacity of a cloud computing system for prioritized users. The capacity mitigation policy can be directed to users of the cloud computing system. The policy engine can be configured to control how the capacity mitigation policy is applied to the cloud computing system. The enforcement layer can be configured to handle incoming resource requests and to enforce resource limits based on the capacity mitigation policy as applied by the policy engine.

Abstract: A transfer learning system is used for the development of neural transformer models pertaining to software engineering tasks. The transfer learning system trains source code domain neural transformer models with attention in various configurations on a large corpus of unsupervised training dataset of source code programs and/or source code-related natural language text. A web service provides the trained models for use in developing a model that may be fine-tuned on a supervised training dataset associated with a software engineering task thereby generating a tool to perform the software engineering task.

Abstract: A text input system is described for inputting text to a computing device. The text input system has a memory storing a composing region comprising a plurality of text items selected by a user for potential input into the computing device. The text input system has a composing region updater which detects one of the plurality of text items as being a designated symbol. The composing region updater is configured to detect a corrective action acting to correct associated text associated with the selected text items and, when the corrective action is detected, to return the plurality of text items including the designated symbol to the composing region.

Abstract: The present disclosure applies trained artificial intelligence (AI) processing adapted to automatically generating transformations of formatted templates. Pre-existing formatted templates (e.g., slide-based presentation templates) are leveraged by the trained AI processing to automatically generate a plurality of high-quality template transformations. In transforming a formatted template, the trained AI processing not only generates feature transformation of objects thereof but may also provide style transformations where attributes associated with a presentation theme may be modified for a formatted template or set of formatted templates. The trained AI processing is novel in that it is tailored for analysis of feature data of a specific type of formatted template.

Abstract: Methods, systems and computer program products are provided for improving performance (e.g., reducing power consumption) of a hardware accelerator (e.g., neural processor) comprising hybrid or analog multiply and accumulate (MAC) processing elements (PEs). Selective variation of the precision of an array of MAC PEs may reduce power consumption of a neural processor. Power may be conserved by dynamically controlling the precision of analog to digital (ADC) output bits for one or more MAC PEs. Dynamic control of ADC output bit precision may be based on precision information determined during training and/or post-training (e.g., quantization) of an artificial intelligence (AI) neural network (NN) model implemented by the neural processor. Precision information may include a range of dynamic precision for each of a plurality of nodes of a computation graph for the AI NN model.

Abstract: The disclosure herein describes changing a mode of operation of a computing device using signals from a pen device. The pen device obtains gesture input data from at least one sensor of the pen device and the obtained gesture input data is compared to at least one gesture pattern. Based on the gesture input data matching the at least one gesture pattern, the pen device transitions to an active state. The pen device detects, via an electrostatic communication channel, an uplink signal from the computing device and sends a signal to change a mode of operation of the computing device by at least one of a network interface or a communication channel, other than the electrostatic communication channel. Changing modes of operation of a computing device provides a flexible, stream-lined way to enhance the user experience of using a computing device with a pen device (e.g., performing an initial pairing process).

Abstract: Systems, methods, and devices are described for enabling a user to import a library into a computer program under development. The library includes a data storage interface, one or more semantic objects, and one or more data manipulation or data analysis operations. A user is able to reference code of the library within the computer program under development to generate a dataset from data obtained via the data storage interface and associate the one or more semantic objects with the dataset to generate a semantically-annotated dataset. Systems, methods, and devices enable, based on the importing: the user to invoke a semantic-guided operation of the library that utilizes the semantically-annotated dataset to infer an aspect of a data manipulation or data analysis operation to be performed on the semantically-annotated dataset; or the suggestion of a data manipulation or data analysis operation to the user based on the semantically-annotated dataset.

Abstract: A multi-battery system implements operations to equalize discharge path impedance. The system includes first and second batteries of different capacities each coupled to a battery rail that supports source load electronics. The system includes charge control electronics configured to decouple the first battery from the battery rail when the discharge path of the first battery and the discharge path of the second battery have unequal impedance and to recouple the first battery to the battery rail when the discharge path of the first battery and the discharge path of the second battery have substantially equal impedance.

Abstract: Methods, systems, and computer storage media for providing a multi-attribute cluster-identifier that supports identifying malicious activity in computing environments. An instance of an activity having an attribute set can be assessed. The attribute set of the instance of the activity is analyzed to determine whether the instance of the activity is a malicious activity. The attribute set of the instance of the activity is compared to a plurality of multi-attribute cluster-identifiers of previous instances of the activity, such that, a determination that the instance of the activity is a malicious activity is made when the attribute set of the instance of the activity corresponds to an identified multi-attribute cluster-identifier. The identified multi-attribute cluster-identifier has a risk score and an attribute set that indicate a likelihood that the instance of the activity is a malicious activity. A visualization that identifies the instance of the activity as a malicious activity is generated.

Abstract: A switching network for effecting point-to-point communication between nodes has a time-varying switching configuration, which causes successive activation and deactivation of multiple channels of the switching network, a first of the channels connecting, when activated, a transmitter node and a first receiver node, and a second of the channels connecting, when activated, the transmitter node and a second receiver node.

Abstract: Cryptographically-secured deferral tickets provided by a minting process that runs in a secure enclave on a computing device reset an authenticated watchdog timer that reboots the device from a hardware-protected recovery operating system to re-image the device into a known good state if the timer expires. The deferral tickets are written to a secure channel using a symmetric key that is provisioned by repurposing an existing Intel SGX (Software Guard Extension) Versioning Support protocol that enables migration of secrets between enclaves that have the same author. In an illustrative embodiment, the deferral ticket minting process and authenticated watchdog timer execute locally to enable automated recovery of the computing device when utilized in far edge infrastructure of a fifth generation (5G) network such as a distributed unit (DU) of a radio access network (RAN).

Abstract: The present disclosure relates to selectively analyzing digital content items from a social networking system to generate a searchable graph object that facilitates visualization of correlations between entities of interest (e.g., brands, products, services, companies), concepts (e.g., domain-specific and/or general terms), hashtags, and other output classes. For example, systems described herein involve collecting images and/or videos that are publicly available via a social networking platform and evaluating content and metadata thereof to identify entities of interest therein and predict various concepts therein to generate a graph object that provides a searchable matrix. The systems herein provide a mechanism for processing a graph query that presents a relational graph showing correlations between the query and the various output classes.

Abstract: A tracing coprocessor that records execution trace data based on a cache coherency protocol (CCP) message. The tracing coprocessor comprises logic that causes the tracing coprocessor to listen on a bus that is communicatively coupled to a primary processor that executes executable code instructions. The logic also causes the tracing coprocessor to, based on listening on the bus, identify at least one CCP message relating to activity at a processor cache. The logic also causes the tracing coprocessor to identify, from the at least one CCP message, a memory cell consumption by the primary processor. The logic also causes the tracing coprocessor to initiate logging, into an execution trace, at least a memory cell data value consumed by the primary processor in connection with execution of at least one executable code instruction.

Abstract: This application relates to video encoding and decoding, and specifically to tools and techniques for using and providing supplemental enhancement information in bitstreams. Among other things, the detailed description presents innovations for bitstreams having supplemental enhancement information (SEI). In particular embodiments, the SEI message includes picture source data (e.g., data indicating whether the associated picture is a progressive scan picture or an interlaced scan picture and/or data indicating whether the associated picture is a duplicate picture). The SEI message can also express a confidence level of the encoder's relative confidence in the accuracy of this picture source data. A decoder can use the confidence level indication to determine whether the decoder should separately identify the picture as progressive or interlaced and/or a duplicate picture or honor the picture source scanning information in the SEI as it is.

Abstract: This application relates to video encoding and decoding, and specifically to tools and techniques for using and providing supplemental enhancement information in bitstreams. Among other things, the detailed description presents innovations for bitstreams having supplemental enhancement information (SEI). In particular embodiments, the SEI message includes picture source data (e.g., data indicating whether the associated picture is a progressive scan picture or an interlaced scan picture and/or data indicating whether the associated picture is a duplicate picture). The SEI message can also express a confidence level of the encoder's relative confidence in the accuracy of this picture source data. A decoder can use the confidence level indication to determine whether the decoder should separately identify the picture as progressive or interlaced and/or a duplicate picture or honor the picture source scanning information in the SEI as it is.

Abstract: Examples of the present disclosure describe systems and methods for multichannel audio speech classification. In examples, an audio signal comprising multiple audio channels is received at a processing device. Each of the audio channels in the audio signal is transcoded to a predefined audio format. For each of the transcoded audio channels, an average power value is calculated for one or more data windows in the audio signal. A correlation value is calculated between the average power value for each audio channel and the combined average power value of the other audio channels in the audio signal. Each of the correlation values (or an aggregated correlation value for the audio channels) is then compared against a threshold value to determine whether the audio signal is to be classified as a speech-based communication. Based on the classification, an action associated with the audio signal may be performed.

Abstract: A method for text compression comprises recognizing a prefix string of one or more text characters preceding a target string of a plurality of text characters to be compressed. The prefix string is provided to a natural language generation (NLG) model configured to output one or more predicted continuations each having an associated rank. If the one or more predicted continuations include a matching predicted continuation relative to the next one or more text characters of the target string, the next one or more text characters are compressed as an NLG-type compressed representation. If no predicted continuations match the next one or more text characters of the target string, a longest matching entry in a compression dictionary is identified. The next one or more text characters of the target string are compressed as a dictionary-type compressed representation that includes the dictionary index value of the longest matching entry.

Abstract: According to examples, an apparatus may include a processor and a memory on which is stored machine-readable instructions that when executed by the processor, may cause the processor to identify configuration information to be used by an on-premise access management service to provide authentication services to applications by users. The processor may also transform the identified configuration information into a transformed set of configuration information to be used by a cloud-based access management service to provide authentication services to the applications by users. In addition, the processor may store the transformed set of configuration information for use by the cloud-based access management service to provide authentication services to the applications by users to migrate authentication of the users from the on-premise access management service to the cloud-based access management service.

Abstract: According to examples, a processor may receive data pertaining to a communication sent over a network by a device, extract a set of characteristics associated with the communication from the received data, and determine whether the extracted set of characteristics meets a predefined similarity threshold with respect to a previously identified set of characteristics, in which the previously identified set of characteristics is assigned with a certain device type. The processor may also, based on a determination that the extracted set of characteristics meets the predefined similarity threshold with respect to the previously identified set of characteristics, assign the device with the certain device type.

Abstract: Systems and methods are provided for training a data model based on training data. The training includes pre-training and fine-tuning the data model based on a combination of an autoregressive (AR) model and a non-autoregressive (NAR) model. Training data may be received and encoded into streams of tokens. A pre-trainer during decoding generates a continuum of data structures of the AR and NAR combined model including a main stream and a series of predicting streams. Masked tokens in predicting streams reference or attend to one or more preceding tokens in the main stream or the preceding predicting streams. A fine-tuner selects streams to generate a trained model according to a target data model. The target data model is determined based on balancing an accuracy constraint and an efficiency constraint for predicting tokens. The decoder acts as abridge between the AR and NAR models in generating a trained data model.

Abstract: A system and method and for searching for an element in and replacement a portion of a video is conducted by retrieving the video and generating a video index for the video, the video index indexing a plurality of elements of the video such as text, audio and video. To search in the vide, a search query is received that includes at least one of a text element, an audio element, an image element, or a video element. Features and embeddings are extracted from the search query before comparing the search query features with the video index to identify a portion of the video that includes one of the text element, audio element, image element or video element of the search query. The identified portion is then automatically replaced with a replacement portion to generate a revised video.

Abstract: A computing system including a classical computing device, including a processor that generates a Haar-random unitary matrix. The processor further computes a single-particle-basis fermion rotation based at least in part on the Haar-random unitary matrix and outputs the single-particle-basis fermion rotation to a quantum computing device. The quantum computing device receives a specification of a fermion wavefunction and further receives the single-particle-basis fermion rotation. The quantum computing device further applies the single-particle-basis fermion rotation to the fermion wavefunction. The quantum computing device further measures the rotated fermion wavefunction to obtain a classical shadow measurement result. The processor of the classical computing device further receives the classical shadow measurement result.

Abstract: A server system is provided that includes one or more processors configured to execute a platform for an online multi-user chat service that communicates with a plurality of client devices of users of the online multi-user chat service that exchanges user chat data between the plurality of client devices. The one or more processors are configured to execute a user chat filtering program that performs filter actions for user chat data exchanged on the platform for the online multi-user chat service. The user chat filtering program includes a plurality of trained machine learning models and a filter decision service that determines a filter action to be performed for target portions of user chat data based on output of the plurality of trained machine learning models for those target portions of user chat data.

Abstract: This document relates to training of machine learning models. One example method involves providing a machine learning model having a first classification layer, a second classification layer, and an encoder that feeds into the first classification layer and the second classification layer. The example method also involves obtaining first training examples having explicit labels and second training examples having inferred labels. The inferred labels are based at least on actions associated with the second training examples. The example method also involves training the machine learning model using the first training examples and the second training examples using a training objective that considers first training loss of the first classification layer for the explicit labels and second training loss of the second classification layer for the inferred labels. The method also involves outputting a trained machine learning model having the encoder and the first classification layer.

Abstract: A computing device, including a processor configured to perform data transfer scheduling for a hardware accelerator including a plurality of processing areas. Performing data transfer scheduling may include receiving a plurality of data transfer instructions that encode requests to transfer data to respective processing areas. Performing data transfer scheduling may further include identifying a plurality of transfer path conflicts between the data transfer instructions. Performing data transfer scheduling may further include sorting the data transfer instructions into a plurality of transfer instruction subsets. Within each transfer instruction subset, none of the data transfer instructions have transfer path conflicts. For each transfer instruction subset, performing data transfer scheduling may further include conveying the data transfer instructions included in that transfer instruction subset to the hardware accelerator.

Abstract: Innovations in phase quantization during speech encoding and phase reconstruction during speech decoding are described. For example, to encode a set of phase values, a speech encoder omits higher-frequency phase values and/or represents at least some of the phase values as a weighted sum of basis functions. Or, as another example, to decode a set of phase values, a speech decoder reconstructs at least some of the phase values using a weighted sum of basis functions and/or reconstructs lower-frequency phase values then uses at least some of the lower-frequency phase values to synthesize higher-frequency phase values. In many cases, the innovations improve the performance of a speech codec in low bitrate scenarios, even when encoded data is delivered over a network that suffers from insufficient bandwidth or transmission quality problems.

Abstract: An application is installed on a computing device from an application package. An origin of the application (e.g., a managed installer for an enterprise, a reputation checking service) is propagated to files written to a storage device of the computing device as part of the installation, such as by writing origin information to the storage device as metadata associated with the file. The origin information for a file, in conjunction with a policy on the computing device specifying one or more trusted origins for applications on the computing device, is used to identify whether a particular action can be taken with and/or by the file. These actions can include, for example, execution of an application from an executable file. If the origin information for a file indicates an origin that is a trusted origin specified by the policy, then the action can be performed.

Abstract: A method for multi-intent searching includes surfacing, via a web browser provided through a network, a search engine UI in a first browser tab, where the search engine UI includes a search box for specifying a search query. The method includes, responsive to user input, entering keystrokes into the search box, surfacing an autocomplete menu adjacent to the search box, and populating the autocomplete menu with suggested search queries related to the entered keystrokes. The method also includes surfacing a pop-out icon corresponding to each suggested search query within the autocomplete menu and, responsive to additional user input including a selection of the pop-out icon corresponding to one of the suggested search queries, launching a second browser tab including search results for the suggested search query, where the autocomplete menu with the suggested search queries is maintained within the first browser tab after the launching of the second browser tab.

Abstract: Techniques are disclosed for deploying functions in a cloud computing environment. Parameters are annotated in a plurality of Helm charts with a predetermined token. Duplicated values in the Helm charts are identified and the predetermined token is reused for the duplicated values. Schema files from the plurality of Helm charts are parsed to extract the predetermined tokens. Input data are received as values for the predetermined tokens. The function is deployed in the cloud computing environment using the values for the predetermined tokens as parameters in the Helm charts.