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學術報告預告:Neural Networks and Deep Learning-Basic Principles and Practical Issues

發布時間:2018-07-14 來源: 作者: 浏覽數:

澳门新葡萄新京學術報告預告

題目:Neural Networks and Deep Learning-Basic Principles and Practical Issues

主講人:盧軍青

間:2018717日上午10:15

點:6205

報告内容:

Deep learning is to use vast amount of data to train neural networks with multi-hidden layers. This talk will introduce the general structures of the artificial neurons and neural networks, and discuss the basic principles and algorithms used in network training, such as feedforward and backpropagation algorithms, stochastic gradient decent (SGD) technique, and activation and cost functions. We will also discuss some of the important practical issues in network training, such as training data pre-processing, parameters initializing, hyperparameters tuning, cross validation, and overfitting.

主講人簡介:

盧軍青:美國東卡大學(East Carolina University)教授,1983年畢業于南開大學物理系,1986年獲南開大學物理系碩士研究生,1991年獲美國加利福尼亞大學爾灣分校物理系博士研究生。曾在肯特州立大學、加利福尼亞大學 、聖地亞哥市表面光學公司、東卡大學任職,發表SCI論文60多篇,獲國内外專利多項,主持美國自然科學基金3項。現為Optics LettersOptical ExpressApplied OpticsIEEE Transactions on Biomedical Engineering 等雜志審稿人。歡迎全校對神經網絡和深度學習感興趣的師生參加。

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