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讲座预告:邓世文教授谈“Effectively and efficiently characterizing manifold of data”

作者:李彦霖   点击:9  发布时间:2019-10-30 15:56:05

时间:1031日(周四)1100-1200

地点:勤园21号楼306学术报告厅

主讲人:邓世文,教授,哈尔滨师范大学数学学院,2012年毕业于哈尔滨工业大学计算学院人工智能与信息处理专业,主要研究方向:优化方法与智能信息处理、模式识别、机器学习、信号处理等,具体涉及以下应用研究内容:声学事件检测、声音场景识别、心音信号分析与识别、遥感图像处理与识别、信号增强等。在IEEE T. SIGNAL. PROCES.IEEE SIGNAL PROC. LET.MECH. SYST. SIGNAL PR.DIGIT SIGNAL PROCESS.等期刊及本领域国际学术会议ICASSPInterspeechICPR等发表学术论文19篇。

内容简介:The manifold assumption is wildly used in maching learning, based on which many mainifold-inspired methods are described, explicitly or Implicitly.

In this report, we provide some results of the autoencoder (AE) in deep learning and our current works as follows:

1) explicit geometric interpretation in contractive AE, denosing AE, and winner-take-all AE;

2) Implicit manifold assumption in sparse coding

3) Fast approximation for primal splitting algorithm with the manifold assumption.