Stochastic Binary Neural Networks for Qualitatively Robust Predictive Model Mapping

• 作者: A. T. Burrell P. Papantoni-Kazakos
• 来源期刊: 通讯、网络与系统学国际期刊(英文)
• 学科: 数学
• 关键词: Qualitative ROBUSTNESS PREDICTIVE Model Mapping STOCHASTIC APPROXIMATION STOCHASTIC BINARY Neural Networks Real-Time Supervised Learning ERGODICITY
• 年，卷（期）: 2012,（9）
• 页码范围: 603-608
• 页数: 6页
• 分类号: O1

摘要

We consider qualitatively robust predictive mappings of stochastic environmental models, where protection against outlier data is incorporated. We utilize digital representations of the models and deploy stochastic binary neural networks that are pre-trained to produce such mappings. The pre-training is implemented by a back propagating supervised learning algorithm which converges almost surely to the probabilities induced by the environment, under general ergodicity conditions.