Abstract: Computing systems, computing apparatuses, computing methods, and computer program products are disclosed for machine learning ranking. An example computing method includes receiving a search query and determining a plurality of machine learning model execution engines based on the search query and a plurality of search result types. The example computing method further includes generating a plurality of subsets of search results based on the search query and the plurality of machine learning model execution engines. The example computing method further includes generating a set of search results comprising at least one search result from each of the plurality of subsets of search results.

Abstract: Computing systems, computing apparatuses, computing methods, and computer program products are disclosed for machine learning ranking. An example computing method includes receiving a search query and determining a plurality of machine learning model execution engines based on the search query and a plurality of search result types. The example computing method further includes generating a plurality of subsets of search results based on the search query and the plurality of machine learning model execution engines. The example computing method further includes generating a set of search results comprising at least one search result from each of the plurality of subsets of search results.

Abstract: Systems, devices, and methods related to audio systems for providing personalized audio zones are provided. An example audio system includes a first speaker to transmit an ultrasonic signal modulated by a first portion of a first audio signal. The audio system further includes a second speaker to transmit a second portion of the first audio signal, where the second portion is in a lower frequency band than the first portion. The audio system further includes a noise canceller to at least attenuate a second audio signal, where the second audio signal is in a lower frequency band than the first portion of the first audio signal.

Abstract: An apparatus, method, and computer program product are provided to adjust and modify input signals used in connection with predictive models by detecting events, such as changes in operating parameters of data objects and/or related systems and calculating adjusted decay rates to be applied to time-series data associated with times prior to an occurrence of an event. In some example implementations, an indication of an event associated with a given datastream is received, in a manner which indicates the change in an operating parameter and the time at which the change occurred. Based at least in part on the indication of the event associated with the datastream, a second decay rate associated with the set of time-series data is determined and applied to the set of time-series data, such that an updated future performance level can be calculated by a predictive model.

Abstract: Computing systems, computing apparatuses, computing methods, and computer program products are disclosed for machine learning ranking. An example computing method includes receiving a search query and determining a plurality of machine learning model execution engines based on the search query and a plurality of search result types. The example computing method further includes generating a plurality of subsets of search results based on the search query and the plurality of machine learning model execution engines. The example computing method further includes generating a set of search results comprising at least one search result from each of the plurality of subsets of search results.

Abstract: In general, embodiments of the present invention provide systems, methods and computer readable media for a predictive recommendation system using predictive models derived from tiered feature data.

Abstract: In an optical detection system, received light can be concentrated and presented to a single-pixel photodetector (or an array of relatively few photodetectors). Concentration of received light can be performed by curved concentrator such as a continuously-curved or faceted reflector. A portion or an entirety of the detector might be blinded (e.g., desensitized) by bright interferers such as the sun. An electro-optic shutter such as a liquid crystal (LC) structure can be used to selectively transmit or mask-off portions of the received light. For example, an LC structure can have regions of selectable opacity for a specified polarization of incident light. The LC structure can be controlled to render certain region opaque, such as to suppress interference from unwanted interferers such as the sun, bright lights, or unwanted reflections. An LC structure can also be used to implement a scanned transmit/receive technique.

Abstract: An apparatus, method, and computer program product are provided to adjust and modify input signals used in connection with predictive models by detecting events, such as changes in operating parameters of data objects and/or related systems and calculating adjusted decay rates to be applied to time-series data associated with times prior to an occurrence of an event. In some example implementations, an indication of an event associated with a given datastream is received, in a manner which indicates the change in an operating parameter and the time at which the change occurred. Based at least in part on the indication of the event associated with the datastream, a second decay rate associated with the set of time-series data is determined and applied to the set of time-series data, such that an updated future performance level can be calculated by a predictive model.

Abstract: An apparatus, method, and computer program product are provided to filter and modify option data objects and weighted values associated with option data objects through the application of specific rule sets based on the relative density of option data objects within a particularized area. In some example implementations, option data objects and related parameters are parsed to identify locations associated with the option data object and a weighted value, such as a weighted value generated by a predictive model. Based at least in part on the location associated with the option data object, a determined location of a user of a mobile device, and location-specific distance criteria, the weighted value associated with the option data object may be modified to reflect distance-related option election probabilities.

Abstract: Computing systems, computing apparatuses, computing methods, and computer program products are disclosed for machine learning ranking. An example computing method includes receiving a search query and determining a plurality of machine learning model execution engines based on the search query and a plurality of search result types. The example computing method further includes generating a plurality of subsets of search results based on the search query and the plurality of machine learning model execution engines. The example computing method further includes generating a set of search results comprising at least one search result from each of the plurality of subsets of search results.

Abstract: An apparatus, method, and computer program product are provided to adjust and modify input signals used in connection with predictive models by detecting events, such as changes in operating parameters of data objects and/or related systems and calculating adjusted decay rates to be applied to time-series data associated with times prior to an occurrence of an event. In some example implementations, an indication of an event associated with a given datastream is received, in a manner which indicates the change in an operating parameter and the time at which the change occurred. Based at least in part on the indication of the event associated with the datastream, a second decay rate associated with the set of time-series data is determined and applied to the set of time-series data, such that an updated future performance level can be calculated by a predictive model.

Abstract: In general, embodiments of the present invention provide systems, methods and computer readable media for a predictive recommendation system using predictive models derived from tiered feature data.

Abstract: An apparatus, method, and computer program product are provided to predict and model the performance of option data objects prior to the introduction of such option data objects into a network environment through the application of specific rule sets that are applied in a multi-stage arrangement on sets of extracted option data object parameters. In some example implementations, option data object parameters are extracted and parsed into sets of categorical and non-categorical parameters, which may be both quantitative and qualitative, and transmitted to one or more predictive models. Through the operation of the predictive models, the option data object parameters are transformed into a weighted value associated with the option data object that reflects a predicted performance level of the option data object and can be used when comparing multiple option data objects against each other.

Abstract: An apparatus, method, and computer program product are provided to filter and modify option data objects and weighted values associated with option data objects through the application of specific rule sets based on the relative density of option data objects within a particularized area. In some example implementations, option data objects and related parameters are parsed to identify locations associated with the option data object and a weighted value, such as a weighted value generated by a predictive model. Based at least in part on the location associated with the option data object, a determined location of a user of a mobile device, and location-specific distance criteria, the weighted value associated with the option data object may be modified to reflect distance-related option election probabilities.

Abstract: A method, computer program product, and apparatus for determining improved data objects are provided. An example method receives a request for a renderable data object from a location source device associated with a user profile including instant location data. The method queries an explicit locations database and an implicit locations database and coranks this multisource locations data. The method compares the coranked locations with one or more object redemption locations of each renderable data object. The method determines a proximity score for each renderable data object and ranks each renderable data object based upon proximity score. The method then identifies a proximate data object having a minimum proximity score and transmits the proximate data object to the location source device.

Abstract: An apparatus, method, and computer program product are provided to predict and model the performance of option data objects prior to the introduction of such option data objects into a network environment through the application of specific rule sets that are applied in a multi-stage arrangement on sets of extracted option data object parameters. In some example implementations, option data object parameters are extracted and parsed into sets of categorical and non-categorical parameters, which may be both quantitative and qualitative, and transmitted to one or more predictive models. Through the operation of the predictive models, the option data object parameters are transformed into a weighted value associated with the option data object that reflects a predicted performance level of the option data object and can be used when comparing multiple option data objects against each other.

Abstract: Embodiments may relate to an audio system for playback of an audio signal, for example in a motor vehicle. The audio system may include a virtualization speaker located in a position that would be in front of a listener of the audio system. The audio system may further include a user speaker located in a position that would be behind a listener of the audio system. In some embodiments the virtualization speaker may be configured to play a virtualization audio signal while the user speakers are configured to play an audio signal which at least partially overlaps the virtualization audio signal. In some embodiments the virtualization audio signal may be at a different volume or a different frequency range than the audio signal. Other embodiments may be described or claimed.

Abstract: A method, computer program product, and apparatus for determining improved data objects are provided. An example method receives a request for a renderable data object from a location source device associated with a user profile including instant location data. The method queries an explicit locations database and an implicit locations database and coranks this multisource locations data. The method compares the coranked locations with one or more object redemption locations of each renderable data object. The method determines a proximity score for each renderable data object and ranks each renderable data object based upon proximity score. The method then identifies a proximate data object having a minimum proximity score and transmits the proximate data object to the location source device.

Abstract: In general, embodiments of the present invention provide systems, methods and computer readable media for a predictive recommendation system using predictive models derived from tiered feature data.

Abstract: In an optical detection system, received light can be concentrated and presented to a single-pixel photodetector (or an array of relatively few photodetectors). Concentration of received light can be performed by curved concentrator such as a continuously-curved or faceted reflector. A portion or an entirety of the detector might be blinded (e.g., desensitized) by bright interferers such as the sun. An electro-optic shutter such as a liquid crystal (LC) structure can be used to selectively transmit or mask-off portions of the received light. For example, an LC structure can have regions of selectable opacity for a specified polarization of incident light. The LC structure can be controlled to render certain region opaque, such as to suppress interference from unwanted interferers such as the sun, bright lights, or unwanted reflections. An LC structure can also be used to implement a scanned transmit/receive technique.