Abstract: The techniques and/or systems described herein are directed to improvements in homomorphic encryption to improve processing speed and storage requirements. For example, the techniques and/or systems can be used on a client device to encode data to be sent to a remote server, to be operated on while maintaining confidentiality of data. For example, data including a real number can be encoded as a polynomial, with the fractional part of the real number encoded as high-order coefficients in the polynomial. Further, real numbers can be approximated and encoded in a polynomial using a fractional base, and/or the encoding can include slot encoding. Thus, the optimized encodings disclosed herein provide an optimized homomorphic encryption scheme.

Abstract: The description relates to 3D gesture recognition. One example gesture recognition system can include a gesture detection assembly. The gesture detection assembly can include a sensor cell array and a controller that can send signals at different frequencies to individual sensor cells of the sensor cell array. The example gesture recognition system can also include a gesture recognition component that can determine parameters of an object proximate the sensor cell array from responses of the individual sensor cells to the signals at the different frequencies, and can identify a gesture performed by the object using the parameters.

Abstract: A method for presenting health notifications begins with creating a plurality of different health notifications, each conveying the same type of information. Each of the different health notifications is provided to a plurality of different users, each user categorized with user health metrics. Post-health notification user activity is tracked for each of the different users. A machine-learning classification machine is trained with tracked user activity, along with corresponding user health metrics, for each of the different health notifications. When provided with user health metrics received from a health-monitoring computing device associated with a user, the machine-learning classification machine chooses a selected health notification for the user from among the different health notifications, the selected notification determined to be more likely than any of the other health notifications to elicit a healthy response from the user. The selected health notification is then sent to the user.

Abstract: The description relates to 3D gesture recognition. One example gesture recognition system can include a gesture detection assembly. The gesture detection assembly can include a sensor cell array and a controller that can send signals at different frequencies to individual sensor cells of the sensor cell array. The example gesture recognition system can also include a gesture recognition component that can determine parameters of an object proximate the sensor cell array from responses of the individual sensor cells to the signals at the different frequencies, and can identify a gesture performed by the object using the parameters.

Abstract: Embodiments described herein are directed to methods and systems for performing neural network computations on encrypted data. Encrypted data is received from a user. The encrypted data is encrypted with an encryption scheme that allows for computations on the ciphertext to generate encrypted results data. Neural network computations are performed on the encrypted data, using approximations of neural network functions to generate encrypted neural network results data from encrypted data. The approximations of neural network functions can approximate activation functions, where the activation functions are approximated using polynomial expressions. The encrypted neural network results data are communicated to the user associated with the encrypted data such that the user decrypts the encrypted data based on the encryption scheme. The functionality of the neural network system can be provided using a cloud computing platform that supports restricted access to particular neural networks.

Abstract: Example apparatus and methods transform a non-metric latent space produced by a matrix factorization process to a higher dimension metric space by applying an order preserving transformation to the latent space. The transformation preserves the order of the results of an inner product operation defined for the latent space. The higher dimension metric space may be queried for the results to different requests. Example apparatus and methods may assign every user i a vector ui in a latent space, and may assign every item j a vector vj in the latent space. The dot product ui·vj represents the score between the user i and the item j. The score represents the strength of the relationship between the user i and the item j. Example apparatus and methods may then apply ranking methodologies (e.g., LSH, K-D trees) to problems including recommendation, targeting, matchmaking, or item to item.

Abstract: A computer management system may track services on multiple computers executing the same workload. Various performance counters may be retrieved from the computers and analyzed to identify those with low deviations and low mean deviations. Statistical tests may then be used to compare the values of a particular computer to the deviation of the group of computers to identify outliers, which may indicate degraded performance and imminent failure of the computer. The management system may analyze any collectable performance related parameter to identify outlying systems.

Abstract: Example apparatus and methods transform a non-metric latent space produced by a matrix factorization process to a higher dimension metric space by applying an order preserving transformation to the latent space. The transformation preserves the order of the results of an inner product operation defined for the latent space. The higher dimension metric space may be queried for the results to different requests. Example apparatus and methods may assign every user i a vector ui in a latent space, and may assign every item j a vector vj in the latent space. The dot product ui·vj represents the score between the user i and the item j. The score represents the strength of the relationship between the user i and the item j. Example apparatus and methods may then apply ranking methodologies (e.g., LSH, K-D trees) to problems including recommendation, targeting, matchmaking, or item to item.

Abstract: Biological entity communication channel techniques are described. In one or more implementations, an apparatus includes a signal conductor having a side that is configured to be disposed proximal to a surface of a biological entity to use at least a part of the biological entity as a transmission channel to transmit a signal received by the signal conductor from an electrical device. The apparatus also includes a ground layer configured to be disposed on an opposing side of the signal conductor from the side of the signal conductor that is configured to be disposed against the surface of the biological entity.

Abstract: A digital personal assistant is described that determines a mental or emotional state of a user based on one or more signals and, based on the determined mental or emotional state, provides the user with feedback concerning an item of content generated thereby or an activity to be conducted thereby. An API is described that can be used by diverse applications and/or services to communicate with the digital personal assistant for the purpose of obtaining information about the current mental or emotional state of the user. Content tagging logic is described that identifies one or more items of content generated or interacted with by the user and stores metadata in association with the identified item(s) of content. The metadata includes information indicative of the current mental or emotional state of the user during the time period when the user generated or interacted with the content.

Abstract: Example apparatus and methods transform a non-metric latent space produced by a matrix factorization process to a higher dimension metric space by applying an order preserving transformation to the latent space. The transformation preserves the order of the results of an inner product operation defined for the latent space. The higher dimension metric space may be queried for the results to different requests. Example apparatus and methods may assign every user i a vector ui in a latent space, and may assign every item j a vector vj in the latent space. The dot product ui·vj represents the score between the user i and the item j. The score represents the strength of the relationship between the user i and the item j. Example apparatus and methods may then apply ranking methodologies (e.g., LSH, K-D trees) to problems including recommendation, targeting, matchmaking, or item to item.

Abstract: The description relates to 3D gesture recognition. One example gesture recognition system can include a gesture detection assembly. The gesture detection assembly can include a sensor cell array and a controller that can send signals at different frequencies to individual sensor cells of the sensor cell array. The example gesture recognition system can also include a gesture recognition component that can determine parameters of an object proximate the sensor cell array from responses of the individual sensor cells to the signals at the different frequencies, and can identify a gesture performed by the object using the parameters.

Abstract: Systems, methods, apparatuses, and computer program products are described for implementing a digital personal assistant. The digital personal assistant is capable of determining that a user has asked a question or made a statement that is intended to engage with a persona of the digital personal assistant. In response to determining that the user has asked such a question or made such a statement, the digital personal assistant provides a response thereto by displaying or playing back a multimedia object associated with a popular culture reference within or by a user interface of the digital personal assistant. Additionally or alternatively, in response to determining that the user has asked such a question or made such a statement, the digital personal assistant provides the response thereto by generating or playing back speech that comprises an impersonation of a voice of a person associated with the popular culture reference.

Abstract: Example apparatus and methods transform a non-metric latent space produced by a matrix factorization process to a higher dimension metric space by applying an order preserving transformation to the latent space. The transformation preserves the order of the results of an inner product operation defined for the latent space. The higher dimension metric space may be queried for the results to different requests. Example apparatus and methods may assign every user i a vector ui in a latent space, and may assign every item j a vector vj in the latent space. The dot product ui·vj represents the score between the user i and the item j. The score represents the strength of the relationship between the user i and the item j. Example apparatus and methods may then apply ranking methodologies (e.g., LSH, K-D trees) to problems including recommendation, targeting, matchmaking, or item to item.

Abstract: A computer system is described for providing intervention suggestion information to a user, for the purpose of changing a psychological state of the user. The information suggestion information identifies at least one recommended intervention, selected from a pool of candidate interventions. Each candidate intervention, in turn, involves a type of computer-related activity with which the user is likely already familiar. The computer system formulates the intervention suggestion information in the form of one or more messages, delivered to one or more user devices, such as a mobile user device, or a mobile user device in conjunction with an ambient presentation device. According to one optional aspect, the computer system chooses the recommended interventions based on context information. According to another aspect, the computer system selects interventions by adopting a particular balance between an exploitation mode and an exploration mode.

Abstract: Search model updates are described. In one or more implementations, a search service uses a model to rank items in a search result, the model formed using an initial set of data. An update is generated using a subsequent set of data, which is formed after the initial set of data, that provides feedback describing user interaction with one or more items in the search result formed using the model, the generating of the update performed without use of at least a portion of the initial set of data. The model and the update are employed to rank items in a search result for a subsequent search.

Abstract: A training system is described herein for generating a prediction model that relies on a feature space with reduced dimensionality. The training system performs this task by producing partitions, each of which corresponds to a subset of aspect values (where each aspect value, in turn, may correspond to one or more attribute values). The training system then produces instances of statistical information associated with the partitions. Each instance of statistical information therefore corresponds to feature information that applies to a plurality of aspect values, rather than a single aspect value. The training system then trains the prediction model based on the feature information. Also described herein is a prediction module that uses the prediction model to make predictions in various online contexts.

Abstract: A computer management system may track services on multiple computers executing the same workload. Various performance counters may be retrieved from the computers and analyzed to identify those with low deviations and low mean deviations. Statistical tests may then be used to compare the values of a particular computer to the deviation of the group of computers to identify outliers, which may indicate degraded performance and imminent failure of the computer. The management system may analyze any collectable performance related parameter to identify outlying systems.

Abstract: A computer management system may track services on multiple computers executing the same workload. Various performance counters may be retrieved from the computers and analyzed to identify those with low deviations and low mean deviations. Statistical tests may then be used to compare the values of a particular computer to the deviation of the group of computers to identify outliers, which may indicate degraded performance and imminent failure of the computer. The management system may analyze any collectable performance related parameter to identify outlying systems.

Abstract: Technologies are described herein for placing search results on a search engine results page (SERP). A query may be received. The query may be transmitted to a plurality of search result providers. A first set of search results and a second set of search results may be received from the search result providers. Intent features may be extracted from the first set of search results. User intent of the second set of search results may be inferred based on the extracted intent features. The first set of search results and the second set of search results may be ranked based on the inferred user intent. The SERP may be rendered according to the ranked first set and second set of search results.