The java code for finding optimal ternary thresholds for neural networks trained using stochastic firing with real weights.
This repository is released for reproducing the results in the following publication
Hande Alemdar, Vincent Leroy, Adrien Prost-Boucle, and Frederic Petrot. “Ternary Neural Networks for Resource- Efficient AI Applications”. In: International Joint Conference on Neural Networks (IJCNN). 2017.
The following repository is required:
https://github.com/slide-lig/tnn_train
Copyright 2017 Université Grenoble Alpes
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.