Pulselight Holdings, Inc.

Sparkcognition, Inc.

Jimmie Goode

Jonathan William Mugan

Laura Hitt

Yuan Qu

Russ Gregory

Sari Andoni

Keith D Moore

Tyler S McDonnell

Junhwan Choi

Yiyun Lan

Gavin Sellers

A recurrent neural network (RNN) method implemented on a computer system is used to produce summaries of unstructured text generated by multiple networks of individuals interacting over time by encoding the unstructured text into intermediate representations and decoding the intermediate representations into summaries of each network. Parameter data for the RNN is obtained by using multiple different versions of the same source texts to train the computer system. The method and computer system can be used to identify which of the networks match a query by determining which network generates the query with low or lowest cost.

Method and system for analyzing entities

A method includes receiving, by a processor, an input data set. The input data set includes a plurality of features. The method includes determining, by the processor, one or more characteristics of the input data set. The method includes, based on the one or more characteristics, adjusting, by the processor, one or more architectural parameters of an automated model generation process. The automated model generation process is configured to generate a plurality of models using a weighted randomization process. The one or more architectural parameters weight the weighted randomization process to adjust a probability of generation of models having particular architectural features. The method further includes executing, by the processor, the automated model generation process to output a mode, the model including data representative of a neural network.

Automated model building search space reduction

Growing community of inventors

Austin, TX, United States of America

Jimmie Goode