Abstract: Systems and methods are provided for performing a video-grounded dialogue task by a neural network model using bi-directional spatial-temporal reasoning. According to some embodiments, the systems and methods implement a dual network architecture or framework. This framework includes one network or reasoning module that learns dependencies between text and video in the direction of spatial?temporal, and another network or reasoning module that learns in the direction of temporal?spatial. The output of the multimodal reasoning modules may be combined to learn dependencies between language features in dialogues. The result joint representation is used as a contextual feature to the decoding components which allow the model to semantically generate meaningful responses to the users. In some embodiments, pointer networks are extended to the video-grounded dialogue task to allow the model to point to specific tokens from multiple source sequences to generate responses.

Abstract: A method to provide multi-objective recommendations. The method includes receiving user input indicating a plurality of objectives, where each of the plurality of objectives indicates a desired goal for a field of interest, receiving user input indicating a plurality of actionable fields, receiving user input indicating selection of one of a plurality of records in a data set, determining, based on applying an evolutionary algorithm, one or more candidate changes to values of the plurality of actionable fields of the selected record, determining, for each of the one or more candidate changes, a multi-objective score for that candidate change, selecting one or more of the one or more candidate changes to recommend to a user based on the multi-objective scores of the one or more candidate changes, and providing, for display to the user, the selected one or more candidate changes as recommended changes.

Abstract: Technologies are provided for tracking learning progress of an end user of a cloud computing platform when the end user is not registered with an external learning platform that provides an external learning application. In response to the end user interacting with virtual learning entities provided at the cloud computing platform, learning progress information with respect to the external learning application is generated. The interaction by the end user takes place in the context of an application provided by the cloud computing platform while in an active web session. The virtual learning entities represent content of the external learning application (e.g., learning content and contextual user information of the external learning application). When a user service of the external learning platform receives a request to persist the learning progress information for the end user, the user service can determine whether a corresponding user account (e.g.

Abstract: Technologies are provided for integrating learning data provided by an external learning platform (ELP) to create a custom learner experience within a context of an application provided by a cloud computing platform (CCP). The system can include the CCP, the ELP, learner APIs that expose a common learning data schema on the CCP, and a user interface platform (UIP). The UIP can include a compiler that transforms source code of UICs of a componentized learner user interface for usage on the CCP, and a bundler that generates a package of UI components (UICs) that are compatible for usage on the CCP. The UICs are specific to the learning data schema shared with the learner APIs. The UIP exports the package to the CCP, which composes the learning data provided via learner APIs and UICs from the package to provide the custom learner experience within the context of the application.

Abstract: Disclosed herein are system, method, and computer program product embodiments for facilitating access to and incorporation of APIs within an application during development, while ensuring that the API satisfies quality constraints. These quality constraints are controlled by the application of rules, which result in a maturity score for the API, in accordance with embodiments. These rules may be provided by a variety of sources for use in scoring the API at various stages. For example, a developer group may control access to developers within the group by applying a ruleset that restricts APIs for applications written by the developer group to a threshold score. This threshold score can limit or restrict APIs that are offered to a developer by an API exchange. Additionally, a ruleset may be applied to enforce a minimum score for submission of an API for inclusion within an API exchange.

Abstract: A compute container system may support logical partitions for various single tenant systems. These logical partitions may be referred to as logical single-tenant system stacks. An operator or release manager for a logical partition may identify a declarative deployment file defining a deployment configuration for one or more of a plurality of logical single-tenant system stacks. The operator may determine a deployment schedule for implementing one or more system updates for the plurality of logical single-tenant system stacks based on the declarative deployment file and implement the system updates based on the determined deployment schedule.

Abstract: In accordance with embodiments, there are provided mechanisms and methods for facilitating actionable insights for performance of web products in database systems according to one embodiment. In one embodiment and by way of example, a method includes dynamically running simulation of modifications to performance factors associated with a web product, and collecting actionable insights associated with the performance factors based on one or more of cost-benefit ratings of the performance factors, one or more delivery platforms, one or more device types. The method may further include recommending, based on the actionable insights, one or more adjustments to one or more of the performance factors to enhance performance of the web product, and facilitating, based on the recommendations, the one or more adjustments to one or more virtual knobs corresponding to the one or more performance factors to facilitate one or more modifications to one or more metrics to enhance the performance of the web product.

Abstract: Monitoring statements in a database environment. Substantially all database query statements to be executed against a database in the database environment are analyzed to determine if a statement has an outlier statistic. Database queries that do not have an associated outlier statistic are serviced. Further analysis is performed for statements having an outlier statistic to determine if the corresponding statement poses a security risk to the database environment.

Abstract: Methods and systems are provided for managing environmental conditions and energy usage associated with a site. One exemplary method of regulating an environment condition at a site involves a server receiving environmental measurement data from a monitoring system at the site via a network, determining an action for an electrical appliance at the site based at least in part on the environmental measurement data and one or more monitoring rules associated with the site, and providing an indication of the action to an actuator for the electrical appliance.

Abstract: Disclosed herein are system, method, and device embodiments for implementing an order management graphical user interface (GUI). An application service may monitor completion of a workflow associated with a purchase order, generate a GUI layout associated with the purchase order, the GUI layout including a graphical workflow frame dimensioned to present a predicted amount of graphical representations associated with the workflow, and a detailed information frame. Further, the application service may generate a first graphical representation representing the purchase order and the order status, generate a graphical area corresponding to an operation of the plurality of operations for providing the product to the customer, determine performance of the operation based on the monitoring, generate a second graphical representation within the graphical area based on the performance of the operation, and generate a connection item between the first graphical representation and the second graphical representation.

Abstract: Systems and methods for unifying question answering and text classification via span extraction include a preprocessor for preparing a source text and an auxiliary text based on a task type of a natural language processing task, an encoder for receiving the source text and the auxiliary text from the preprocessor and generating an encoded representation of a combination of the source text and the auxiliary text, and a span-extractive decoder for receiving the encoded representation and identifying a span of text within the source text that is a result of the NLP task. The task type is one of entailment, classification, or regression. In some embodiments, the source text includes one or more of text received as input when the task type is entailment, a list of classifications when the task type is entailment or classification, or a list of similarity options when the task type is regression.

Abstract: Disclosed are examples of systems, apparatus, methods, and computer program products for generating content objects using an integrated development environment. In some implementations, an integrated development environment is displayed. A request to generate or update an educational content object can be processed, and a presentation including metadata selection options can be provided. After a selection of one of the metadata selection options is received, the presentation can be updated. A different request is received from a rich text editor provided in a new presentation, and the new presentation can be updated.

Abstract: Disclosed are examples of systems, apparatus, methods and computer program products for automation of network security policy analysis and deployment. A server system can obtain a system input comprising two versions of a policy output. The system can generate a severity characteristic that indicates a severity of deploying the second version of the policy output. The system can then determine whether to deploy the second version of the policy output based on the severity characteristic. The system can then, in response to determining that the second version of the policy output is to be deployed, deploy the second version of the policy output to one of a plurality of clouds.

Abstract: Methods and apparatus for updating a denormalized database object after updating, deleting, or inserting a record in a source database object are described. A first operation on a source database object that involves a record of the source database object being updated, deleted, or inserted is performed. A first part of a corresponding second operation involving a respective record of the denormalized database object being updated, deleted, or inserted is performed. A query result that references an aggregate field of a set of records in the denormalized database object is altered. The altering includes an aggregation operation using values in the query result being performed and altering that part of the query result that includes the aggregate field of the set of records. A second part is optionally performed to complete the corresponding second operation and update the denormalized database object.

Abstract: Hybrid training of deep networks includes a multi-layer neural network. The training includes setting a current learning algorithm for the multi-layer neural network to a first learning algorithm. The training further includes iteratively applying training data to the neural network, determining a gradient for parameters of the neural network based on the applying of the training data, updating the parameters based on the current learning algorithm, and determining whether the current learning algorithm should be switched to a second learning algorithm based on the updating. The training further includes, in response to the determining that the current learning algorithm should be switched to a second learning algorithm, changing the current learning algorithm to the second learning algorithm and initializing a learning rate of the second learning algorithm based on the gradient and a step used by the first learning algorithm to update the parameters of the neural network.

Abstract: Methods, systems, and devices supporting differential support for frequent pattern (FP) analysis are described. Some database systems may analyze data sets to determine FPs of data attributes within the data sets. However, if data distributions for different types of data attributes vary greatly, more frequent data attribute types may skew the FPs away from the less frequent types. To reduce the noise of common attributes while maintaining sensitivity to the less common attributes, the database system may implement multiple minimum support (e.g., frequency) thresholds. For example, the database system may adaptively categorize the different data attribute types into data categories based on their distributions and may dynamically determine support thresholds for the categories. Using different minimum support thresholds for different data categories allows the system to filter out data attribute patterns based on the distributions of the data attribute types in the pattern.

Abstract: A group of recommendations related to an item, such as an item of content presented to a user in a page, can be ranked according to a probability distribution that is iteratively updated with each user interaction. For practical implementations, a click stream of interactions may be logged, and then applied in a batch process to update the probability distribution on any suitable schedule independent of the timing of incoming user interactions.

Abstract: Methods and systems are provided for copying one database to another, such as where a database is upgraded from an earlier version to a later version. Database catalog files are used to copy the database table definitions, with appropriate changes made as needed between the first and second databases or database versions.

Abstract: Computing systems, for example, multi-tenant systems create data centers in a cloud platform using a cloud platform infrastructure language that is cloud platform independent. The system receives a cloud platform independent declarative specification describing a new datacenter to be created and a customization specification for customizing the data center. The system compiles the declarative specification along with the customization specification to generate a metadata representation of the data center. The metadata representation is used to generate a data center on a target cloud platform. Different customization specifications can be provided to generate different customized datacenters based on the same declarative specification. For example, the different customized data centers may implement different policies, for example, network policies, security policies, and so on.

Abstract: Mechanisms and techniques for providing continuous integration and continuous deployment (CI/CD) for data lake applications are disclosed. Assembly of code for an app is managed with a CI platform to create a container within a shared environment within which the app runs. The container is isolated from other containers and bundles software, libraries and configuration files and can communicate with other containers through defined channels. The shared environment provides a platform for running the app. The app writes to one or more tables maintained in the shared environment. Assembly of subsequent versions of code for the app is managed by the CI platform. Deployment of the assembled subsequent version of the code to the container is managed by the CI platform. Integration tests are run on the deployed subsequent version of the code with the CI platform. The subsequent version of the code replaces the app in the shared environment when integration testing is complete.