LICENSE

Copyright (c) <2019>
<Nankai University, Tianjin, China>
<Advanced Digital Sciences Center, Singapore>
<University of Illinois at Urbana-Champaign>
All rights reserved.


General terms and conditions for use of the uL2Q design. The design 
comprising "uL2Q" and the documentation provided with them are 
copyright Cheng Gong, Ye Lu, Tao Li, Yao Chen, Deming Chen, 
the Nankai University, Tianjin, China, 
the Advanced Digital Sciences Center, Singapore 
and the University of Illinois at Urbana-Champaign.

Only non-commercial, not-for-profit use of this design is permitted. No part 
of this software design may be incorporated into a commercial product without the 
written consent of the authors.  Similarly, use of 
this software to assist in the development of new commercial applications is 
prohibited, unless the written consent of the authors is obtained.

This software is provided "as is" with no warranties or guarantees of support. 
All users of the software design must take the copy from this site. You may modify or 
use the source code for other non-commercial, not-for-profit research endeavours,
provided that all copyright attribution on the source code is retained, and the
original or modified source code is not redistributed, in whole or in part, or
included in or with any commercial product, except by written agreement with
the authors, and full and complete attribution for use of the code is given in
any resulting publications. Subject to these conditions, the software is
provided free of charge to all interested parties.

When referencing this particular open-source software in a publication, please 
cite the following publication:
Cheng Gong, Ye Lu, Tao Li, Xiaofan Zhang, Cong Hao, Deming Chen and Yao Chen, "uL2Q: An Ultra-low Loss Quantization Method for DNN", The 2019 International Joint Conference on Neural Networks (IJCNN).