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Building Energy Consumption Prediction: An Extreme Deep Learning Approach 期刊论文
ENERGIES, 2017, 卷号: 10, 期号: 10, 页码: 1-20
作者:  Li, Chengdong;  Ding, Zixiang;  Zhao, Dongbin;  Yi, Jianqiang;  Zhang, Guiqing
浏览  |  Adobe PDF(1918Kb)  |  收藏  |  浏览/下载：312/49  |  提交时间：2017/12/30
Building Energy Consumption  Deep Learning  Stacked Autoencoders  Extreme Learning Machine  
Parameter Identifiability in Statistical Machine Learning: A Review 期刊论文
NEURAL COMPUTATION, 2017, 卷号: 29, 期号: 5, 页码: 1151-1203
作者:  Ran, Zhi-Yong;  Hu, Bao-Gang
浏览  |  Adobe PDF(466Kb)  |  收藏  |  浏览/下载：326/97  |  提交时间：2017/07/18
Parameter Identifiability  Statistical Machine Learning  
Deep Reinforcement Learning With Visual Attention for Vehicle Classification 期刊论文
IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS, 2017, 卷号: 9, 期号: 4, 页码: 356-367
作者:  Zhao, Dongbin;  Chen, Yaran;  Lv, Le
浏览  |  Adobe PDF(3192Kb)  |  收藏  |  浏览/下载：1034/539  |  提交时间：2017/05/08
Convolutional Neural Network (Cnn)  Reinforcement Learning  Vehicle Classification  Visual Attention  
Optimal Budget Allocation Across Search Advertising Markets 期刊论文
INFORMS JOURNAL ON COMPUTING, 2015, 卷号: 27, 期号: 2, 页码: 285-300
作者:  Yang, Yanwu;  Zeng, Daniel;  Yang, Yinghui;  Zhang, Jie
浏览  |  Adobe PDF(1107Kb)  |  收藏  |  浏览/下载：591/238  |  提交时间：2015/09/17
Sponsored Search  Budget Allocation  Budget Strategy  Search Markets  
Pure-Strategy Nash Equilibria of GSP Keyword Auction 期刊论文
JOURNAL OF THE ASSOCIATION FOR INFORMATION SYSTEMS, 2012, 卷号: 13, 期号: 2, 页码: 57-87
作者:  Li, Linjing;  Zeng, Daniel;  Zhao, Huimin
浏览  |  Adobe PDF(622Kb)  |  收藏  |  浏览/下载：336/83  |  提交时间：2015/08/12
Keyword Advertising  Stability  Generalized Second-price  Sponsored Search  Nash Equilibrium  
Dynamic dual adjustment of daily budgets and bids in sponsored search auctions 期刊论文
DECISION SUPPORT SYSTEMS, 2014, 卷号: 57, 期号: 0, 页码: 105-114
作者:  Zhang, Jie;  Yang, Yanwu;  Li, Xin;  Qin, Rui;  Zeng, Daniel
浏览  |  Adobe PDF(983Kb)  |  收藏  |  浏览/下载：340/95  |  提交时间：2015/08/12
Sponsored Search Auction  Budget Adjustment  Continuous Reinforcement Learning  Dynamic Adjustment