今日头条人工智能实验室与清华大学国家重点实验室将于 6 月 22 日（星期四）联合举办第二期 AI 技术沙龙。本期沙龙邀请到上海科技大学信息科学与技术学院的马毅教授作为主讲嘉宾。带来题为「高维 (视觉) 数据的低维结构与深度模型」的主题分享。
- 时间：6 月 22 日（星期四）19:00
- 地点：清华 FIT 楼多功能厅
In this talk, we will discuss a class of models and techniques that can effectively model and extract rich low-dimensional structures in high-dimensional data such as images and videos, despite nonlinear transformation, gross corruption, or severely compressed measurements. This work leverages recent advancements in convex optimization from Compressive Sensing for recovering low-rank or sparse signals that provide both strong theoretical guarantees and efficient and scalable algorithms for solving such high-dimensional combinatorial problems. We illustrate how these new mathematical models and tools could bring disruptive changes to solutions to many challenging tasks in computer vision, image processing, and pattern recognition.
We will also illustrate some emerging applications of these tools to other data types such as 3D range data, web documents, image tags, bioinformatics data, audio/music analysis, etc. Throughout the talk, we will discuss strong connections of algorithms from Compressive Sensing with other popular data-driven models such as Deep Neural Networks, providing some new perspectives to understand Deep Learning.
Yi Ma has been a Professor of the School of Information and Science and Technology, ShanghaiTech University, China since 2014. From 2009 to early 2014, he was a Principal Researcher and the Research Manager of the Visual Computing group at Microsoft Research in Beijing. From 2000 to 2011, he was an Associate Professor at the Electrical & Computer Engineering Department of the University of Illinois at Urbana-Champaign. His main research interest is in computer vision, high-dimensional data analysis, and systems theory. He has written two textbooks「An Invitation to 3-D Vision」published by Springer in 2004, and「Generalized Principal Component Analysis」published by Springer in 2016. Yi Ma received his Bachelors』 degree in Automation and Applied Mathematics from Tsinghua University (Beijing, China) in 1995, a Master of Science degree in EECS in 1997, a Master of Arts degree in Mathematics in 2000, and a PhD degree in EECS in 2000, all from the University of California at Berkeley. Yi Ma received the David Marr Best Paper Prize at the International Conference on Computer Vision 1999, the Longuet-Higgins Best Paper Prize (honorable mention) at the European Conference on Computer Vision 2004, and the Sang Uk Lee Best Student Paper Award with his students at the Asian Conference on Computer Vision in 2009. He also received the CAREER Award from the National Science Foundation in 2004 and the Young Investigator Award from the Office of Naval Research in 2005. He was an associate editor of IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), the International Journal of Computer Vision (IJCV), and IEEE transactions on Information Theory. He is currently an associate editor of the IMA journal on Information and Inference, SIAM journal on Imaging Sciences, IEEE Signal Processing Magazine. He served as a Program Chair for ICCV 2013 and is a General Chair for ICCV 2015. He is a Fellow of IEEE. He is ranked the World's Highly Cited Researchers of 2016 by Clarivate Analytics of Thomson Reuters and is among Top 50 of the Most Influential Authors in Computer Science of the World, ranked by Semantic Scholar, reported by Science Magazine, April 2016.
今日头条人工智能实验室成立于 2016 年，依托今日头条的海量数据，专注于人工智能领域的前沿研究，并将研究成果应用于今日头条的产品中，利用人工智能帮助内容的创作、分发、互动、管理。同时，实验室也将针对人工智能相关领域内长期性和开放性问题进行研究，帮助公司实现对未来发展的构想，促进人类信息与知识交流的效率与深度。