Abstract: Systems and methods for model evaluation. A model is evaluated by performing a decomposition process for a model output, relative to a baseline input data set.

Abstract: Systems and methods for generating and processing modeling workflows are disclosed. In some examples, a reference distribution of scores generated by a model is determined. The reference distribution of scores is recorded in a structured database. One or more unexpected scores are detected during execution of the model. To detect the one or more unexpected scores, a production distribution of scores is compared with the reference distribution of scores recorded in the structured database. The production distribution of scores is generated by the model for a production input data set. An alert is then provided to an external system, when an alert condition is determined to be satisfied based on the comparison. The alert indicates detection of the one or more unexpected scores.

Abstract: Systems and methods for generating and processing modeling workflows.

Abstract: An application monitoring infrastructure that enables application configuration changes on multiple machines across multiple OS types to be tracked by identifying data containers that are to be monitored for changes, detecting a change to a monitored data container, and storing data representative of a changed version of the monitored data container responsive to detecting that the monitored container was changed. The data containers that are to be monitored for changes are identified from templates, and a unique template is provisioned for each of the applications.

Abstract: An application monitoring infrastructure that enables application configuration changes on multiple machines across multiple OS types to be tracked by identifying data containers that are to be monitored for changes, detecting a change to a monitored data container, and storing data representative of a changed version of the monitored data container responsive to detecting that the monitored container was changed. The data containers that are to be monitored for changes are identified from templates, and a unique template is provisioned for each of the applications.

Abstract: An application monitoring infrastructure that enables application configuration changes on multiple machines across multiple OS types to be tracked by identifying data containers that are to be monitored for changes, detecting a change to a monitored data container, and storing data representative of a changed version of the monitored data container responsive to detecting that the monitored container was changed. The data containers that are to be monitored for changes are identified from templates, and a unique template is provisioned for each of the applications.

Abstract: Systems and methods for generating and processing modeling workflows.

Abstract: Systems and methods for model evaluation. A model is evaluated by performing a decomposition process for a model output, relative to a baseline input data set.

Abstract: An application monitoring infrastructure that enables application configuration changes on multiple machines across multiple OS types to be tracked by identifying data containers that are to be monitored for changes, detecting a change to a monitored data container, and storing data representative of a changed version of the monitored data container responsive to detecting that the monitored container was changed. The data containers that are to be monitored for changes are identified from templates, and a unique template is provisioned for each of the applications.

Abstract: Techniques are disclosed for automatic remediation of application performance degradations caused by configuration changes. In one embodiment, a learning module keeps track of application configuration changes and subsequent effects on the application's performance. The learning module creates new potential remediation rules based on correlations between such configuration changes and performance degradations or improvements. The learning module affirms such potential rules if the correlation between the configuration changes and degradations or improvements are repeatedly observed, and vice versa.

Abstract: An application monitoring infrastructure enables application configuration changes on multiple machines across multiple OS types to be tracked, and correlated to performance degradation and outages by receiving change event data associated with change events occurring at each computer in the computer system, each change event data including an identifier for the associated change event, a path to a data container that was changed, a time stamp representative of when the data container was changed, an identifier for an application that is affected by the change to the data container, and the time stamp representative of when the monitored data container was changed, determining a time at which correlation is to be carried out and a target application for which correlation is to be carried out, and identifying change events associated with the target application that have time stamps that are within a predetermined proximity to the determined time.

Abstract: This invention relates to a method of providing progressive on-line group purchasing of goods and services including the steps of selecting articles to be purchased, receiving a target group size and price, creating a group of target size from among friends in at least one social network, communicating separate purchasing and payment information to a retailer's server, and receiving from said retailer's server separate proofs of purchase for each one of the group members.

Abstract: An application monitoring infrastructure that enables application configuration changes on multiple machines across multiple OS types to be tracked by identifying data containers that are to be monitored for changes, detecting a change to a monitored data container, and storing data representative of a changed version of the monitored data container responsive to detecting that the monitored container was changed. The data containers that are to be monitored for changes are identified from templates, and a unique template is provisioned for each of the applications.

Abstract: An application monitoring infrastructure that enables application configuration changes on multiple machines across multiple OS types to be tracked by identifying data containers that are to be monitored for changes, detecting a change to a monitored data container, and storing data representative of a changed version of the monitored data container responsive to detecting that the monitored container was changed. The data containers that are to be monitored for changes are identified from templates, and a unique template is provisioned for each of the applications.

Abstract: In a large network, it can be difficult to pinpoint and track down the causes of breaches of established policies. A policy compliance server allows traversal of notifications according to breaches, organizes the breaches (vulnerabilities and violation) according to severity and recurrence, and identifies related rules, network entities and configuration changes, which may be related to the breach. An integrated graphical user interface (GUI) provides efficient, timely traversal and analysis of rule breaches across the network to allow quick, efficient identification of the underlying cause or condition of the rule breach. A discoverer gathers configuration data including notifications of changes, alerts, and conditions in the network that are pertinent to the rule breaches. A compliance engine evaluates the configuration data against the rules to identify breaches.

Abstract: Techniques are disclosed for automatic remediation of application performance degradations caused by configuration changes. In one embodiment, a learning module keeps track of application configuration changes and subsequent effects on the application's performance. The learning module creates new potential remediation rules based on correlations between such configuration changes and performance degradations or improvements. The learning module affirms such potential rules if the correlation between the configuration changes and degradations or improvements are repeatedly observed, and vice versa.

Abstract: An application monitoring infrastructure that enables application configuration changes on multiple machines across multiple OS types to be tracked by identifying data containers that are to be monitored for changes, detecting a change to a monitored data container, and storing data representative of a changed version of the monitored data container responsive to detecting that the monitored container was changed. The data containers that are to be monitored for changes are identified from templates, and a unique template is provisioned for each of the applications.

Abstract: An application monitoring infrastructure that enables application configuration changes on multiple machines across multiple OS types to be tracked by identifying data containers that are to be monitored for changes, detecting a change to a monitored data container, and storing data representative of a changed version of the monitored data container responsive to detecting that the monitored container was changed. The data containers that are to be monitored for changes are identified from templates, and a unique template is provisioned for each of the applications.

Abstract: An application monitoring infrastructure that enables application configuration changes on multiple machines across multiple OS types to be tracked by identifying data containers that are to be monitored for changes, detecting a change to a monitored data container, and storing data representative of a changed version of the monitored data container responsive to detecting that the monitored container was changed. The data containers that are to be monitored for changes are identified from templates, and a unique template is provisioned for each of the applications.

Abstract: An application monitoring infrastructure enables application configuration changes on multiple machines across multiple OS types to be tracked, and correlated to performance degradation and outages by receiving change event data associated with change events occurring at each computer in the computer system, each change event data including an identifier for the associated change event, a path to a data container that was changed, a time stamp representative of when the data container was changed, an identifier for an application that is affected by the change to the data container, and the time stamp representative of when the monitored data container was changed, determining a time at which correlation is to be carried out and a target application for which correlation is to be carried out, and identifying change events associated with the target application that have time stamps that are within a predetermined proximity to the determined time.