Annealing Contour Monte Carlo for Neural Network Training

机译：退火轮廓蒙特卡洛神经网络训练

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In this article we propose a general Monte Carlo optimization algorithm, the so called annealing contour Monte Carlo algorithm. The algorithm is illustrated by a neural network training example and compared with simulated annealing. The new algorithm is superior to simulated annealing in both theory and practice. The numerical results show that the new algorithm has made a drastic improvement over simulated annealing in neural network training in whatever computational times or the quality of the solutions.

机译：在本文中，我们提出了一种通用的蒙特卡洛优化算法，即所谓的退火轮廓蒙特卡洛算法。该算法由神经网络训练示例进行说明，并与模拟退火进行比较。新算法在理论和实践上均优于模拟退火。数值结果表明，无论在什么计算时间或求解质量上，新算法都比神经网络训练中的模拟退火有了很大的改进。

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《International Conference on Cybernetics and Information Technologies, Systems and Applications(CITSA2004) and 10th International Conference on Information Systems Analysis and Synthesis(ISAS2004) vol.3》|2004年|130-135|共6页
会议地点 OrlandoFL(US)
作者
Faming Liang;
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Department of Statistics, Texas AM University College Station, TX 77843, USA;

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原文格式 PDF
正文语种 eng
中图分类通信;
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专利

1. Annealing stochastic approximation Monte Carlo algorithm for neural network training [J] . Faming Liang Machine Learning . 2007,第3期

机译：神经网络训练的退火随机逼近蒙特卡罗算法
2. Evidence evaluation for Bayesian neural networks using contour Monte Carlo [J] . Liang FM Neural computation . 2005,第6期

机译：基于轮廓蒙特卡洛的贝叶斯神经网络证据评估
3. A MONTE CARLO-BASED METHOD FOR ASSESSING THE MEASUREMENT UNCERTAINTY IN THE TRAINING AND USE OF ARTIFICIAL NEURAL NETWORKS [J] . Coral Rodrigo, Flesch Carlos A., Penz Cesar A., Metrology and Measurement Systems: Metrologia i Systemy Pomiarowe . 2016,第2期

机译：基于蒙特卡洛方法的人工神经网络训练和使用中的测量不确定度评估
4. Annealing Contour Monte Carlo for Neural Network Training [C] . Faming Liang International Conference on Cybernetics and Information Technologies, Systems and Applications(CITSA2004) and 10th International Conference on Information Systems Analysis and Synthesis(ISAS2004) vol.3 . 2004

机译：退火轮廓蒙特卡洛神经网络训练
5. Markov Chain Monte Carlo Bayesian predictive framework for artificial Neural Network Committee modeling and simulation. [D] . Goodrich, Michael S. 2014

机译：马尔可夫链蒙特卡洛贝叶斯预测框架用于人工神经网络委员会建模和仿真。
6. Modelling spatially-resolved diffuse reflectance spectra of a multi-layered skin model by artificial neural networks trained with Monte Carlo simulations [O] . Sheng-Yang Tsui, Chiao-Yi Wang, Tsan-Hsueh Huang, 2018

机译：通过蒙特卡洛模拟训练的人工神经网络对多层皮肤模型的空间分辨漫反射光谱建模
7. Annealing stochastic approximation Monte Carlo algorithm for neural network training [O] . Faming Liang 2007

机译：用于神经网络训练的退火随机近似蒙特卡罗算法
8. Constructing Cross-Linked Polymer Networks Using Monte Carlo Simulated Annealing Technique for Atomistic Molecular Simulations. [R] . Elder, R. M., Sirk, T. W., Andzelm, J. W. 2014

机译：用蒙特卡罗模拟退火技术构建交联聚合物网络用于原子分子模拟。

Annealing Contour Monte Carlo for Neural Network Training

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