Abstract: Systems and methods for resource allocation are described. The systems and methods include receiving utilization data for computing resources shared by a plurality of users, updating a pricing agent using a reinforcement learning model based on the utilization data, identifying resource pricing information using the pricing agent, and allocating the computing resources to the plurality of users based on the resource pricing information.

Abstract: A system and method for content distribution without tracking is described. The system and method includes determining that device identifiers are not available for a first digital content channel; identifying a first cluster of users and a second cluster of users based on the determination that device identifiers are not available; providing first content and second content via the first digital content channel; monitoring user interactions on the first digital content channel to obtain a first conversion rate for users in the first cluster that receive the first content and a second conversion rate for users in the second cluster that receive the second content; computing a cross-cluster treatment effect based on the first conversion rate and the second conversion rate; computing a treatment effect for the first content based on the cross-cluster treatment effect; and providing the first content to a subsequent user based on the treatment effect.

Abstract: Systems and methods for diversity auditing are described. The systems and methods include identifying a plurality of images; detecting a face in each of the plurality of images using a face detection network; classifying the face in each of the plurality of images based on a sensitive attribute using an image classification network; generating a distribution of the sensitive attribute in the plurality of images based on the classification; and computing a diversity score for the plurality of images based on the distribution.

Abstract: A control system facilitates active management of a streaming data system. Given historical data traffic for each data stream processed by a streaming data system, the control system uses a machine learning model to predict future data traffic for each data stream. The control system selects a matching between data streams and servers for a future time that minimizes a cost comprising a switching cost and a server imbalance cost based on the predicted data traffic for the future time. In some configurations, the matching is selected using a planning window comprising a number of future time steps dynamically selected based on uncertainty associated with the predicted data traffic. Given the selected matching, the control system may manage the streaming data system by causing data streams to be moved between servers based on the matching.

Abstract: Methods and systems disclosed herein relate generally to systems and methods for generating simulated images for enhancing socio-demographic diversity. An image-generating application receives a request that includes a set of target socio-demographic attributes. The set of target socio-demographic attributes can define a gender, age, and/or race of a subject that are non-stereotypical for a particular occupation. The image-generating application applies the a machine-learning model to the set of target socio-demographic attributes. The machine-learning model generates a simulated image depicts a subject having visual characteristics that are defined by the set of target socio-demographic attributes.

Abstract: Information associated with a data packet sent to or from a network interface associated with a cluster node is obtained. The information associated with the data packet is correlated to a particular computing unit associated with the cluster node. The information associated with the data packet and information associated with the particular computing unit is aggregated across processes running on the particular computing unit. The aggregated information associated with the particular computing unit is provided to a flow log analyzer.

Abstract: A transceiver device port configuration and monitoring system includes a networking device having a networking device wireless communication system, a port, and a wireless identification system associated with the port. A transceiver device is connected to the port and includes a wireless reader system that retrieves a port identifier for the port from the wireless identification system, and a transceiver device wireless communication system that the transceiver device uses to wirelessly advertise the connection of the transceiver device to the port. In response to receiving the wireless advertisement of the connection of the transceiver device to the port, the networking device uses the networking device wireless communication system to establish a wireless session with the transceiver device, retrieves configuration information from the transceiver device via the wireless session, uses the configuration information to configure the port for operation with the transceiver device, and monitors the port.

Abstract: Systems and methods are described for performing dynamic time warping using diffusion wavelets. Embodiments of the inventive concept integrate dynamic time warping with multi-scale manifold learning methods. Certain embodiments also include warping on mixed manifolds (WAMM) and curve wrapping. The described techniques enable an improved data analytics application to align high dimensional ordered sequences such as time-series data. In one example, a first embedding of a first ordered sequence of data and a second embedding of a second ordered sequence of data may be computed based on generated diffusion wavelet basis vectors. Alignment data may then be generated for the first ordered sequence of data and the second ordered sequence of data by performing dynamic time warping.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that determine target policy parameters that enable target policies to provide improved future performance, even in circumstances where the underlying environment is non-stationary. For example, in one or more embodiments, the disclosed systems utilize counter-factual reasoning to estimate what the performance of the target policy would have been if implemented during past episodes of action-selection. Based on the estimates, the disclosed systems forecast a performance of the target policy for one or more future decision episodes. In some implementations, the disclosed systems further determine a performance gradient for the forecasted performance with respect to varying a target policy parameter for the target policy.

Abstract: In implementations of systems for generating recommendations, a computing device implements a recommendation system to receive prior interaction data describing prior interactions of entities with items. The recommendation system processes the prior interaction data and segments the entities into a first set and a second set. The entities included in the first set have greater numbers of prior interactions with the items than the entities included in the second set. The recommendation system then generates subset data describing a subset of the entities in the first set. This subset excludes entities having numbers of the prior interactions with the items below a threshold. The recommendation system forms a recommendation model based on the subset data and the system uses the recommendation model to generate a recommendation for display in a user interface.

Abstract: In implementations of systems for generating recommendations, a computing device implements a recommendation system to receive prior interaction data describing prior interactions of entities with items. The recommendation system processes the prior interaction data and segments the entities into a first set and a second set. The entities included in the first set have greater numbers of prior interactions with the items than the entities included in the second set. The recommendation system then generates subset data describing a subset of the entities in the first set. This subset excludes entities having numbers of the prior interactions with the items below a threshold. The recommendation system forms a recommendation model based on the subset data and the system uses the recommendation model to generate a recommendation for display in a user interface.

Abstract: A transceiver device port configuration and monitoring system includes a networking device having a networking device wireless communication system, a port, and a wireless identification system associated with the port. A transceiver device is connected to the port and includes a wireless reader system that retrieves a port identifier for the port from the wireless identification system, and a transceiver device wireless communication system that the transceiver device uses to wirelessly advertise the connection of the transceiver device to the port. In response to receiving the wireless advertisement of the connection of the transceiver device to the port, the networking device uses the networking device wireless communication system to establish a wireless session with the transceiver device, retrieves configuration information from the transceiver device via the wireless session, uses the configuration information to configure the port for operation with the transceiver device, and monitors the port.

Abstract: A system includes a first device having a first physical layer transceiver (PHY) and a first port that is coupled to the first PHY and that operates in a mode. The system also includes a second device having a second PHY and a second port that is coupled to the second PHY and that operates in a mode. The second device provides, through the second port via a cable coupled to the first port to the first device and prior to advertising the at least one mode that the second port is configured to operate in, a second PHY ability of the second PHY. The second device receives a first PHY ability of the first PHY and determines that a mismatch exists between the first and second PHY abilities. In response to the mismatch, the second device adjusts the operation of the second PHY to correct the mismatch.

Abstract: A system includes a first device having a first physical layer transceiver (PHY) and a first port that is coupled to the first PHY and that operates in a mode. The system also includes a second device having a second PHY and a second port that is coupled to the second PHY and that operates in a mode. The second device provides, through the second port via a cable coupled to the first port to the first device and prior to advertising the at least one mode that the second port is configured to operate in, a second PHY ability of the second PHY. The second device receives a first PHY ability of the first PHY and determines that a mismatch exists between the first and second PHY abilities. In response to the mismatch, the second device adjusts the operation of the second PHY to correct the mismatch.