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首页 >> 新闻公告 >> 学术报告 >> 5月2日(周三)下午4:00悉尼大学刘同亮博士学术报告 --标签噪声学习
5月2日(周三)下午4:00悉尼大学刘同亮博士学术报告 --标签噪声学习
2018-05-02 11:12

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报告题目:标签噪声学习(Learning with Label Noise

人:刘同亮 博士

    位:悉尼大学

    间:201852日周三下午4:00

    点:东南大学自动化学院会议室(四牌楼校区)

邀请人/主持人:魏海坤 教授

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欢迎各位老师和研究生参加!

 

报告摘要:

Large-scale training data boost the performances of supervised learning but also burdens us with the laborious and expensive labelling task. Some cheap ways are developed to label the data. The obtained labels are therefore likely to be erroneous. A natural question is that can we avoid the adverse effects of the label noise and get the optimal solutions just as learning from the clean data? Or, how to mitigate the adverse effects?

In this talk, the recent advances in both theoretical foundations and algorithm designs for label noise will be surveyed. We will first introduce the different types of label noise and the challenges behind them. We will explain the well-designed algorithms or surrogate losses which can provably learn from the corrupted labels efficiently. We will finally give some insights of open questions about label noise.

 

报告人简介:

Tongliang Liu is currently a Lecturer (Assistant Professor) with the School of Information Technologies and the Faculty of Engineering and Information Technologies, and a core member in the UBTECH Sydney AI Centre, at The University of Sydney. He received the BEng degree in electronic engineering and information science from the University of Science and Technology of China, and the PhD degree from the University of Technology Sydney. His research interests include statistical learning theory, computer vision, and optimisation. He has authored and co-authored 40+ research papers including IEEE T-PAMI, T-NNLS, T-IP, ICML, CVPR, and KDD.

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