Abstract: A method is implemented by a controller executed on at least one processor. The method provides pre-authorized access to a robotic process automation for a resource associated with a job. The method includes causing, by the controller, the robotic process automation to assume a user identity during an authentication flow to enable access by the robotic process automation to a resource. The method includes issuing, by the controller, tokens to the robotic process automation during the authentication flow. The method includes enabling, by the controller via the tokens, the identity service that governs the resource to participate in operations of the controller to provide the pre-authorized access to the robotic process automation.

Abstract: Methods, systems, and computer programs are presented for labeling datasets. An example method can include generating rules for labeling data records within a first dataset. The rules can indicate an extent to which a data record matches query criteria. The method can further include generating an aggregated label for the corresponding data record based on the rules and training a machine learning model using the first dataset and the aggregated label. The method can include receiving an indication of user engagement and combining the indication of user engagement with the aggregated label to generate a score.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for traffic flow classification using machine learning. In some implementations, a communication device includes an anomaly detector comprising a machine learning model trained to predict whether data traffic patterns differ from a set of observed traffic patterns present in a set of training data. The communication device includes a traffic classifier comprising a machine learning model trained to predict a quality of service (QoS) class for network connections or data flows. The communication device is configured to evaluate network connections or data flows using the anomaly detector. The communication device may (i) use the traffic classifier to predict QoS classes for traffic that the anomaly detector predicts to be similar to the observed traffic patterns, and (ii) store data traffic that the anomaly detector predicts to be different from the observed traffic patterns.

Abstract: Techniques for incorporating sequence encoders into machine-learned models where the sequence encoders operate on bag of words (BOW) input are provided. Tokens that are associated with online activities of an entity are identified. Machine-learned embeddings that correspond to the tokens are identified. Based on one or more ordering criteria that are independent of the temporal occurrence of the online activities of the entity, an order of the machine-learned embeddings is determined. Based on the order, the machine-learned embeddings are inputted to a sequence encoder that generates output. Based on the output, a machine learned model that includes the sequence encoder generates a score. A content item is selected based on the score. The content item is transmitted over a computer network to a computing device.

Abstract: Described herein is machine learning model comprising a neural network that is trained to generate a ranking score for an online job posting. The neural network takes as input a variety of input features, including at least a first input feature that is an encoded representation of a search query as generated by a first Transformer encoder, an encoded representation of a job title as generated by a second Transformer encoder, and an encoded representation of a company name as generated by a third Transformer encoder. Once a plurality of online job postings are ranked, some subset of the plurality are presented in a user interface, ordered based on their respective ranking scores.

Abstract: Computer-implemented systems and methods for diagnosing and correcting connectivity problems in a network are provided. The method includes obtaining, at a network node disposed at an edge of the network, measurements of one or more attributes of network traffic exchanged between a content server and a client device via the network. The network traffic is associated with streaming video content transmitted from the content server to the client device over the network. The method also includes analyzing the one or more attributes of the network traffic to estimate Quality of Experience (QoE) performance metrics related to the streaming video content at the client device, and adjusting one or more network operating parameters of the network responsive to QoE performance metrics falling below a predetermined threshold.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for traffic flow classification using machine learning. In some implementations, a communication device includes an anomaly detector comprising a machine learning model trained to predict whether data traffic patterns differ from a set of observed traffic patterns present in a set of training data. The communication device includes a traffic classifier comprising a machine learning model trained to predict a quality of service (QoS) class for network connections or data flows. The communication device is configured to evaluate network connections or data flows using the anomaly detector. The communication device may (i) use the traffic classifier to predict QoS classes for traffic that the anomaly detector predicts to be similar to the observed traffic patterns, and (ii) store data traffic that the anomaly detector predicts to be different from the observed traffic patterns.

Abstract: Computer-implemented systems and methods for diagnosing and correcting connectivity problems in a network are provided. The method includes obtaining, at a network node disposed at an edge of the network, measurements of one or more attributes of network traffic exchanged between a content server and a client device via the network. The network traffic is associated with streaming video content transmitted from the content server to the client device over the network. The method also includes analyzing the one or more attributes of the network traffic to estimate Quality of Experience (QoE) performance metrics related to the streaming video content at the client device, and adjusting one or more network operating parameters of the network responsive to QoE performance metrics falling below a predetermined threshold.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system obtains a validation configuration containing declarative specifications of fields in a data set and validation rules to be applied to the data set, wherein the validation rules include a field in the data set, a type of validation to be applied to the field, and a parameter for managing a validation failure during evaluation of the validation rules with the data set. Next, the system automatically applies the validation rules to the data set within a workflow for generating the data set to produce validation results indicating passing or failing of the validation rules by the data set. The system then outputs the validation results for use in managing the data set.

Abstract: The disclosed embodiments provide a system for performing profile-driven data validation. During operation, the system obtains a validation configuration containing declarative specifications of fields in a data set and validation rules to be applied to the data set. Next, the system analyzes the data set based on the validation configuration to produce a set of metrics related to the data set and stores the metrics in a profile for the data set. The system also matches a metric in the profile to the type of validation associated with a validation rule in the validation configuration. Finally, the system applies the validation rule to a value of the metric in the profile to produce a validation result for the validation rule.

Abstract: A federated identity verification system includes an identity provider that provides security tokens ultimately to one or more relying parties for access by the client to services at a relying party. Specifically, the relying party can validate the security token from an identity provider (whether directly or via a client) when verifying that the received security token conforms to security configuration data previously exchanged with the identity provider. To establish the trust relationship, the identity provider and one or more relying parties exchange security configuration information through an agreed-to communication channel. The security configuration information indicates the settings that the other party needs to use for establishing, maintaining, and/or monitoring the trust relationship. The communication channel allows both parties to flexibly and continually synchronize changes to security configurations, and thus maintain, change, or end the trust relationship automatically, as desired.

Abstract: Methods and processes are claimed for optimal design of hydraulic fracturing jobs, and in particular, methods and processes for selecting the optimal amount of proppant-carrying fluid to be pumped into the fracture (which is a crucial parameter in hydraulic fracturing) wherein these design parameters are obtained, ultimately from a priori formation/rock parameters, from pressure-decline data obtained during both linear and radial flow regimes, and by analogy with a related problem in heat transfer, in addition the claimed methods and processes also include redundant verification means.