.png){kind=icon}
返回
Ray-guided global optimization method for training neural networks
.png){kind=icon}
PRE
AI
DOI：10.1016/S0925-2312(99)00158-7.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
A novel method for globally searching to find the good minima is proposed in this paper. Starting from a local minimum, the weight space around it is scanned with the process being guided by terrain-independent emanating rays. During the search, starting points for further exploration are identified and used to find corresponding local minima. Based on the correct classification rate (CCR) on the validation data, the best minimum is found. (C) 2000 Elsevier Science B.V. All rights reserved.
期刊
IF:
6.5
论文数:
2.5W
被引数:
6.5W
机构
暂无机构信息
引用论文
Allogeneic versus autologous blood transfusion and survival after radical prostatectomy (CME).png)
Transfusion
OAAI
TransfusionIF0
OAAI分享收藏Development and comparison of different artificial intelligence-based models for viscosity of in-situ cross-linked acids基于人工智能的不同模型在原位交联酸粘度方面的开发与比较
PREAI
分享收藏A Comparison ofNannochloropsis salinaGrowth Performance in Two Outdoor Pond Designs: Conventional Raceways versus the ARID Pond with Superior Temperature Management两种室外池塘设计中 Nannochloropsis salina 生长性能的比较: 常规跑道与具有优越温度管理的干旱池塘OAAI
OAAI分享收藏 没有更多内容
没有更多内容