Abstract: One or more computer processors responsive to neural network run-time, reduce one or more sets of maximum activations along a hidden dimension respectively associated with one or more activation tensors and one or more layers of a neural network. The one or more computer processors compute an interquartile range (IQR) clip threshold for each reduced set for each sequence dimension in the neural network. The one or more computer processors clip one or more activations based on respective computed IQR clip thresholds. The one or more computer processors quantize the clipped activations.

Abstract: The present application relates to systems for generating new variants from an existing corpus of documents and methods for using the same. The systems and methods generally comprise a corpus of documents and one or more types of variety provided by a user. The system generates one or more documents that are variants of the documents in the corpus of documents.

Abstract: The present application relates to systems for generating new variants from an existing corpus of documents and methods for using the same. The systems and methods generally comprise a corpus of documents and one or more types of variety provided by a user. The system generates one or more documents that are variants of the documents in the corpus of documents.

Abstract: A method includes applying at least one tag to at least one data element stored in a database the tag having at least one associated rule, utilizing the at least one associated rule to generate at least one variant of the data element, and storing the at least one variant in the database.

Abstract: A method includes applying at least one tag to at least one data element stored in a database the tag having at least one associated rule, utilizing the at least one associated rule to generate at least one variant of the data element, and storing the at least one variant in the database.

Abstract: A method of tuning a decision network can include a series of steps. The steps can include identifying a deviation between a correct interpretation of a data item and an incorrect interpretation of the data item. In a decision network including a hierarchical set of nodes and leaves, a path of traversed nodes in the decision network resulting in the deviation can be determined. The nodes can correspond to queries. A measure of goodness at a node in the path can be calculated using at least one new query as a replacement for an existing query to determine whether the measure of goodness improves using the new query compared to the old query. If the measure of goodness improves, at least one new query can be selected and the decision network can be regrown from the node down through the leaves using the at least one new query at the node.

Abstract: A method of tuning a decision network can include a series of steps. The steps can include identifying a deviation between a correct interpretation of a data item and an incorrect interpretation of the data item. In a decision network including a hierarchical set of nodes and leaves, a path of traversed nodes in the decision network resulting in the deviation can be determined. The nodes can correspond to queries. A measure of goodness at a node in the path can be calculated using at least one new query as a replacement for an existing query to determine whether the measure of goodness improves using the new query compared to the old query. If the measure of goodness improves, at least one new query can be selected and the decision network can be regrown from the node down through the leaves using the at least one new query at the node.