International Business Machines Corporation

Rensselaer Polytechnic Institute

Chunheng Jiang

Chuang Gan

Pin-Yu Chen

Bo Wu

Tejaswini Pedapati

Jianxi Gao

An output layer is removed from a pre-trained neural network model and a neural capacitance probe unit with multiple layers is incorporated on top of one or more bottom layers of the pre-trained neural network model. The neural capacitance probe unit is randomly initialized and a modified neural network model is trained by fine-tuning the one or more bottom layers on a target dataset for a maximum number of epochs, the modified neural network model comprising the neural capacitance probe unit incorporated with multiple layers on top of the one or more bottom layers of the pre-trained neural network model. An adjacency matrix is obtained from the initialized neural capacitance probe unit and a neural capacitance metric is computed using the adjacency matrix. An active model is selected using the neural capacitance metric and a machine learning system is configured using the active model.

Growing community of inventors

Troy, NY, United States of America

Chunheng Jiang