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Closed-Form Solutions in Low-Rank Subspace Recovery Models and Their Implications
澳门新葡8455最新网站:2016年10月21日 16:03 点击数:

报告人:林宙辰

报告地点:澳门新葡8455最新网站108室

报告澳门新葡8455最新网站:2016年10月25日星期二15:30-16:30

邀请人:

报告摘要:

In recent years, in parallel to sparse models, low-rank models also develop significantly, in particular in subspace recovery problems. Besides robustness, low-rank subspace recovery models may have closed form solutions. This property further makes low-rank models distinct from sparse models. The results are both surprising and elegant. Moreover, they also open doors to better solutions, faster numerical algorithms, and interesting applications. In this talk, I will present my recent work in this line.

主讲人概况:

林宙辰,北京大学信息科学技术新葡京最新官网教授,博士生导师,“东师学者”讲座教授,2016年获得国家杰出青年科学基金资助。2000年他从北京大学获得应用数学博士学位,研究兴趣为计算机视觉,图像处理,机器学习,模式识别与数值优化。他是国际模式识别学会会士(IAPR Fellow),也是模式识别与机器学习领域国际顶级期刊IEEE Transactions on Pattern Analysis and Machine Intelligence 与 International Journal of Computer Vision的副主编,已经发表多篇高水平科研论文。

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