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A tentative schedule for the 2024 IMS-China Conference
(This is only a draft as of Sa 2024.06.15)
The 2024 IMS-China International Conference on Statistics and Probability will be hosted by Ningxia University and held on Saturday, July 6, 2024 to Monday, July 8, 2024 (July 6 for conference registration) at Yinchuan City in Ningxia, China (https://conf.koushare.com/conf/2024IMS; 400 people registered already J).
Day 0 (Sa 07/06) for conference registration only
Day 1 (Su 07/07) morning opening ceremony (8:20-8:40 am; brief remarks by university officials and IMS-China leaders)
Day 1 (Su 07/07) morning block 1 (8:40-9:40 am; 1st keynote lecture)
Speaker: Susan Murphy; Chair: Jianqing Fan
Day 1 (Su 07/07) morning group photo and tea break (9:40-10:10 am)
Day 1 (Su 07/07) morning block 2 (10:10-11:10 am; 2nd keynote lecture)
Speaker: Shige Peng; Chair: Fuzhou Gong
Day 1 (Su 07/07) morning block 3 (11:10 am-12:10 pm; 3rd keynote lecture) Speaker: Song Xi Chen; Chair: Peter Bühlmann
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Keynote lecture abstracts
1). Song Xi Chen, Peking University
Title: High Dimensional Ensemble Kalman Filter
Abstract:
The ensemble Kalman Filter (EnKF), as a fundamental data assimilation approach, has been widely used in many fields of earth science, engineering and beyond. However, there are several unknown theoretical aspects of the EnKF, especially when the state variable is of high dimensional accompanied with high resolution observation and physical models. This paper first proposes several high dimensional EnKF methods which provide consistent estimators for the important forecast error covariance and the Kalman gain matrix. It then studies the theoretical properties of the EnKF under both the fixed and high dimensional state variables, which provides the mean square errors of the analysis states to the underlying oracle states offered by the Kalman filter and gives the much needed insight into the roles played by forecast error covariance on the accuracy of the EnKF. The accuracy of the data assimilation under the misspecified physical model is also considered. Numerical studies on the Lorenz-96 and the Shallow Water Equation models illustrate that the proposed high dimensional EnKF algorithms perform better than the standard EnKF methods as they provide more robust and accurate assimilated results. A joint work with Wang Shouxia and Sun Haoxun.
2). Susan Murphy, Harvard University
Title: Online Reinforcement Learning in Digital Health Interventions
Abstract:
In this talk I will discuss first solutions to some of the challenges we face in developing online RL algorithms for use in digital health interventions targeting patients struggling with health problems such as substance misuse, hypertension and bone marrow transplantation. Digital health raises a number of challenges to the RL community including different sets of actions, each set intended to impact patients over a different time scale; the need to learn both within an implementation and between implementations of the RL algorithm; noisy environments and a lack of mechanistic models. In all of these settings the online line algorithm must be stable and autonomous. Despite these challenges, RL, with careful initialization, with careful management of bias/variance tradeoff and by close collaboration with health scientists can be successful. We can make an impact!
3). Shige Peng, Shandong University
Title: Nonlinear Expectation Algorithms in Machine Learning
Abstract:
Most machine learning algorithms are directly related to the concept of expectation. In particular, the analysis and calculation of the expected value of the loss function directly and deeply involve the optimization problem of the expected loss functional. But in most cases, people often make a very heavy assumption about the data samples, that is, the samples are required to be i.i.d., but it is well-known that the real world's situation is often far from these conditions. In fact, this problem has become a well-known open major issue in the field of machine learning. In this talk, we give more realistic assumptions: we only need to assume that the data sample is “nonlinear iid”, e.g., iid under nonlinear expectations. Based on this more relaxed condition we obtain a very robust algorithm. The theoretical foundation is the law of large numbers and central limit theorem in the framework of sublinear expectations.
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Day 1 (Su 07/07) lunch break (12:10-2:00 pm)
Statistics invited sessions (31 in total and allocated)
Probability invited sessions (13 in total and allocated)
Day 1 (Su 07/07) afternoon block 1 (2:00-3:50 pm; 7 invited sessions)
IS01：Organizer: Jianqing Fan, Princeton University
Session title: Statistical Machine Learning in the age of AI
Session chair: Jianqing Fan, Princeton University
Speakers:
Peter Bühlmann, ETH Zurich
Jun Liu, Harvard University
Yingying Fan, University of Southern California
Weijie Su, University of Pennsylvania
IP01：Organizer: Juan Li, Shandong University
Session title: Stochastic analysis and related topics
Chair: Juan Li, Shandong University,
Speakers:
Yongsheng Song, Chinese Academy of Sciences,
Falei Wang, Shandong University
Qingmeng Wei, Northeast Normal University
Huilin Zhang, Shandong University
IS02: Organizer: Runze Li, Pennsylvania State University
Session title: Recent Advances in High-Dimensional Data Modeling
Session chair: Guanghui Wang, China East Normal University
Speakers:
Changcheng Li, Dalian University of Technology
Haojie Ren, Shanghai Jiaotong University
Guanghui Wang, China East Normal University
Songshan Yang, Renmin University of China
IS03: Organizer: Regina Liu, Rutgers University
Session title: Advances in Learning and Complex Inference Problems
Session chair: Jinchi Lv, University of Southern California
Speakers:
Han Xiao, Rutgers University
Yang Feng, New York University
Ye Tian, Columbia University
Guanyang Wang, Rutgers University
IS04: Organizer: Hans-Georg Müller, University of California, Davis
Session title: Statistical Models for Non-standard Data
Session chair: Yichao Wu, University of Illinois at Chicago
Speakers:
Yaqing Chen, Rutgers University
Asger Morville, Seoul National University
Yichao Wu, University of Illinois at Chicago
Fang Yao, Peking University
IP02: Organizer: Feng-Yu Wang, Tianjin University
Session title: Stochastic Analysis and Geometry
Chair: Feng-Yu Wang, Tianjin University
Speakers:
Bo Wu, Fudan University
Li-Juan Cheng, Hangzhou Normal University
Xing Huang, Tianjin University
Panpan Ren, City University of Hong Kong
IP03: Organizer: Xicheng Zhang, Beijing Institute of Technology
Session title: Recent development of stochastic differential equations
Chair：Xicheng Zhang, Beijing Institute of Technology
Speakers:
Wei Xu，Beijing Institute of Technology
Xuhui Peng, Hunan Normal University
Xiaolong Zhang，Beijing Institute of Technology
Mengyu Cheng, Beijing Institute of Technology
Day 1 (Su 07/07) afternoon tea break (3:50-4:10 pm)
Day 1 (Su 07/07) afternoon block 2 (4:10-6:00 pm; 7 invited sessions)
IS05: Organizer: Aurore Delaigle, University of Melbourne
Session title: Analysis of Curves
Session chair: Tianying Wang, Colorado State University
Speakers:
Zhenhua Lin, National University of Singapore
Ruoxu Tan, Tongji University
Tianying Wang, Colorado State University
Wei Huang, University of Melbourne
IS06: Organizer: Yingying Fan, University of Southern California
Session title: Statistical Learning and Inference in the Era of Big Data
Session chair: Yingying Fan, University of Southern California
Speakers:
Jianqing Fan, Princeton University
Xin Tong, University of Southern California
Yaqi Duan, New York University
Kaizheng Wang, Columbia University
IP04: Organizer: Tiefeng Jiang, University of Minnesota
Session title: Random Matrices and High Dimensional Statistics.
Chair: Wei Xiong, University of International Business and Economics
Speakers:
Zhigang Bao, Hong Kong University of Science and Technology
Zeng Li, Southern University of Science and Technology
Tiefeng Jiang, University of Minnesota (U.S.)
Ke Wang，Hong Kong University of Science and Technology
IS07: Organizer: Jun S. Liu, Harvard University
Session title: From Neural Networks to Statistical Networks
Session chair: Jun S. Liu, Harvard University
Speakers:
Huimin Cheng, Boston University
Qian Lin, Tsinghua University
Quan Zhou, Texas A&M University
Ke Deng, Tsinghua University
IS08: Organizer: Annie Qu, University of California, Irvine
Session title: Modern Statistical Inference and Predictions for Complex Data
Session chair: Guo Yu, University of California, Santa Barbara
Speakers:
Yu Shen, MD Anderson Cancer Center
Guo Yu, University of California, Santa Barbara
Yu Chen, University of Science and Technology of China
Xueqin Wang, University of Science and Technology of China
IP05: Organizer: Zhonggen Su, Zhejiang University
Session title: Stein’s Methods and Probability Concentration Inequalities
Chair：Guangjun Shen, Anhui Normal University
Speakers:
Hanchao Wang，Shandong University
Zhuosong Zhang，Southern University of Science and Technology
Xiequan Fan，Northeastern University at Qinhuangdao
Guozheng Dai，Zhejiang University
IS09: Organizer: Harrison H. Zhou, Yale University
Session title: Recent Developments of Mathematical Statistics
Session chair: Yuefeng Han, University of Notre Dame
Speakers:
Qiyang Han, Rutgers University
Yuefeng Han, University of Notre Dame
Kyoung Hee (Arlene) Kim, Korea University
Anderson Ye Zhang, University of Pennsylvania
Day 2 (M 07/08) morning block 1 (8:00-9:50 am; 8 invited sessions)
IS10: Organizer: Jianqing Fan, Princeton University
Session title: Advances in Analysis of Big and Complex Data
Session chair: Jianqing Fan, Princeton University
Speakers:
Krishna Balasubramanian, University of California, Davis
Kai Zhang, University of North Carolina, Chapel Hill
Elynn Chen, New York University
Zhao Chen, Fudan University
IS11: Organizer: Yang Feng, New York University
Session title: Recent Advances in Transfer Learning and Federated Learning
Session chair: Yang Feng, New York University; yang.feng@nyu.edu
Speakers:
Junlong Zhao, Beijing Normal University
Xinyu Zhang, University of Science and Technology of China
Ruoyu Wang, Harvard University
Haolei Weng, Michigan State University
IS12: Organizer: Jian Huang, The Hong Kong Polytechnic University
Session title: Topics in Statistical Machine Learning
Chair: Jian Huang,The Hong Kong Polytechnic University
Speakers
Long Feng, The University of Hong Kong
Ting Li, The Hong Kong Polytechnic University
Junhui Wang, The Chinese University of Hong Kong
Cun-Hui Zhang, Rutgers University (U.S.)
IP06: Organizer: Shanjian Tang, Fudan University
Chair：Jun Peng, Central South University
Session title：Stochastic System and Control
Speakers：
Linlin Tian, Donghua University
Jun Peng, Central South University
Jianjun Zhou, Northwest A&F University
Shanjian Tang, Fudan University
IS13: Organizer: Huixia Judy Wang, George Washington University
Session title: Advances in Statistical Learning with Applications in Time Series, Network Analysis, and Biomedical Studies
Session chair: Yuguo Chen, University of Illinois-Urbana Champaign
Speakers:
Jinyuan Liu, Vanderbilt University Medical Center
Shuo Chen, University of Maryland
Yuguo Chen, University of Illinois-Urbana Champaign
Ting Zhang, University of Georgia
IP07: Organizer: Jian Wang, Fujian Normal Univeristy
Session title: Stochastic Analysis
Chair：Jian Wang, Fujian Normal Univeristy
Speakers：
Jianhai Bao，Tianjin University
Xin Chen, Shanghai Jiao Tong Univerisity
Lujing Huang, Fujian Normal University
Shukai Chen, Fujian Normal University
IS14: Organizer: Lan Wang, University of Miami
Session title: Innovative Statistical Methods for Data with Complex Structures
Session chair: Wei Ma, Renmin University
Speakers:
Xiucai Ding, University of California, Davis
Hao Helen Zhang, University of Arizona
Lixing Zhu, Beijing Normal University
Wei Ma, Renmin University
IS15: Organizer: Wenyang Zhang, University of Macau
Session title: Recent Developments in Time Series and Panel Data Analysis
Chair: Wenyang Zhang, University of Macau
Speakers:
Qianqian Zhu, Shanghai University of Finance and Economics
Guodong Li, University of Hong Kong
Rongmao Zhang, Zhejiang University
Wenyang Zhang, University of Macau
Day 2 (M 07/08) morning tea break (9:50-10:10 am)
Day 2 (M 07/08) morning block 2 (10:10 am-12:00 pm; 8 invited sessions)
IP08: Organizer: Zenghu Li, Beijing Normal University
Session title: Branching processes and applications
Chair: Hui He, Beijing Normal University
Speakers:
Zhiqiang Gao, Beijing Normal University
Hui He, Beijing Normal University
Peisen Li, Beijing Institute of Technology
Xu Yang, North Minzu University
IS16: Organizer: Weijie Su, University of Pennsylvania
Session title: Recent Advances in Large Language Models from Statistical Perspectives
Chair: Fengnan Gao, University College Dublin, Ireland
Speakers:
Linjun Zhang, Rutgers University, U.S.A.
Xiang Li, University of Pennsylvania, U.S.A.
Yue Xing, Michigan State University, U.S.A.
Yu Pan, The Hong Kong University of Science and Technology
IS17: Organizer: Xueqin Wang, University of Science and Technology of China
Session title: Current Advances in Statistical Inference and Learning Beyond Euclidean Spaces
Chair: Jin Zhu, London School of Economics and Political Science (U.K.)
Speakers:
Jianqing Shi, Southern University of Science and Technology
Hui Huang, Renmin University of China
Roulin Wang, East China Normal University
Jin Zhu, London School of Economics and Political Science (U.K.)
IS18: Organizer: Fang Yao, Peking University
Session title: Complex and Functional structured statistical inference
Chair: Fang Yao, Peking University
Speakers:
Jing Lei, Carnegie Mellon University (U.S.)
Wei Zhong, Xiamen University
Jiguo Cao, Simon Fraser University (Canada)
Decai Liang, Nankai University (China)
IS19: Organizer: Xinyu Zhang, Chinese Academy of Sciences
Chair：Xinyu Zhang, Chinese Academy of Sciences
Session title： Model Averaging and related topics
Speakers:
Yang Li, Renmin University of China
Dalei Yu, Xi'an Jiaotong University
Yuying Sun, Chinese Academy of Sciences
Huihang Liu, University of Science and Technology of China
IP09: Organizer: Xiangchan Zhu, Chinese Academy of Sciences
Session title: Stochastic partial differential equation
Chair: Xiangchan Zhu, Chinese Academy of Sciences
Speakers:
Jianliang Zhai, University of Science and Technology of China
Guohuan Zhao, Academy of Mathematics and Systems Science, Chinese Academy of Sciences
Rangrang Zhang, Beijing Institute of Technology
Weina Wu, Nanjing University of Finance and Economics
IS20: Organizer: Zhongyi Zhu, Fudan University
Session title: Distributed Statistical Inference
Chair: Deyuan Li, Fudan University
Speakers：
Deyuan Li, Fudan University
Xingdong Feng, Shanghai University of Finance and Economics
Yanlin Tang, East China Normal University
Puying Zhao, Yunnan University
IS21: Organizer: Changliang Zou, Nankai University
Session title: Modern robust statistical learning methods
Chair: Xiaodong Yan, Shandong University Speakers:
Xiaodong Yan, Shandong University
Rong Jiang, Shanghai Polytechnic University
Sheng Fu, Nankai University
Yajie Bao, Shanghai Jiao tong University
Day 2 (M 07/08) lunch break (12:00-2:00 pm)
Day 2 (M 07/08) afternoon block 1 (2:00-3:50 pm; 8 invited sessions)
IS22: Organizer: Ming-Yen Cheng, Hong Kong Baptist University
Session title: Statistical analysis of complex high-dimensional data
Chair: Yang Feng, New York University, yang.feng@nyu.edu
Speakers:
Lucy Xia, Hong Kong University of Science and Technology
Le Zhou, Hong Kong Baptist University
Shunan Yao, Hong Kong Baptist University
Lijia Wang, City University of Hong Kong
IP10: Organizer: Fuzhou Gong, Chinese Academy of Science
Session title: Stochastic finance and microstructure of financial markets
Chair: Kai He, Chinese Academy of Science
Speakers:
Youcheng Lou, Chinese Academy of Science
Deqing Zhou, Central University of Finance and Economics
Hong Liu, Northeast Normal University
Xiao Kai, Guizhou University of Finance and Economics
IS23：Organizer：Qizhai Li, Chinese Academy of Sciences
Session title：Some Statistical developments in multivariate analysis
Chair：Qizhai Li, Chinese Academy of Sciences
Speakers:
Wenjun Xiong, Guangxi Normal University
Juan Ding, Hohai University
Yongfeng Wu, Chinese Academy of Sciences
Xiaoyu Zhang, Chinese Academy of Sciences
IP11: Organizer: Wei Liu, Wuhan University
Session title: Large deviation and stochastic analysis
Chair: Lijun Bo, Xidian University
Speakers:
Lijun Bo, Xidian University
Hui Jiang, Nanjing University of Aeronautics and Astronautics
Yiming Jiang, Nankai University
Guangjun Shen, Anhui Normal University
IS24：Organizer: Xinyuan Song, The Chinese University of Hong Kong
Session title: Modern Statistical Inference and Machine Learning
Chair: Xiangnan Feng, Fudan University
Speakers:
Ben Dai, The Chinese University of Hong Kong
Kai Kang, Sun Yat-sen University
Xinzhou Guo, Hong Kong University of Science and Technology
Jiasheng Shi, The Chinese University of Hong Kong (Shenzhen)
IS25: Organizer: Jiaming Xu, Duke University
Session title: High-Dimensional Statistics and Networks
Session chair: Pengkun Yang, Tsinghua University
Speakers:
Hang Du, Massachusetts Institute of Technology
Fengnan Gao, University College Dublin
Pengkun Yang, Tsinghua University
Mingao Yuan, North Dakota State University
IS26: Organizer: Peng Zhao, Jiangsu Normal University
Session title: Statistical Frontiers in Reliability and Cyber Risk
Chair: Maochao Xu, Illinois State University
Speakers:
Zhouping Li, Lanzhou University
Xiaoxiao Hu, Lanzhou University
Gaofeng Da, Nanjing University of Aeronautics and Astronautics
Weiyong Ding, Jiangsu Normal University
IS27: Organizer: Liping Zhu, Renmin University of China
Session title: Independence Test and Association Analysis
Chair: Liping Zhu, Renmin University of China
Speakers：
Qing Cheng, Southwest University of Finance and Economics
Kai Xu, Anhui Normal University
Yaowu Zhang, Shanghai University of Finance and Economics
Yeqing Zhou, Tongji University
Day 2 (M 07/08) afternoon tea break (3:50-4:10 pm)
Day 2 (M 07/08) afternoon block 2 (4:10-6:00 pm; 6 invited sessions)
IS28: Organizer: Jinyuan Chang, Southwest University of Finance and Economics
Chair：Lei Chen, Southwest University of Finance and Economics
Session title: Complex data analysis
Speakers:
Lei Chen, Southwest University of Finance and Economics
Wei Zhou, Southwest University of Finance and Economics
Fengting Yi, Yunnan University
Chenlong Li, Taiyuan University of Technology
IS29: Organizer: Zhao Chen, Fudan University
Session title: Advancements in High-Dimensional Statistical Methods: Efficiency, Robustness, and New Estimators
Chair: Zhao Chen, Fudan University
Speakers:
Shaojun Guo, Renmin University of China
Yuqian Zhang, Renmin University of China
Huijuan Zhou, Shanghai University of Finance and Economics
Dan Wang, New York University, Shanghai
IS30: Organizer: Edgar Dobriban, University of Pennsylvania
Session title: Random Matrix Theory, High-Dimensional Statistics, and Machine Learning
Session chair: Zhixiang Zhang, University of Macau
Speakers:
Jiang Hu, Northeast Normal University
Xiaocong Xu, Hong Kong University of Science and Technology
Tiefeng Jiang, Chinese University of Hong Kong, Shenzhen
Cosme Louart, Chinese University of Hong Kong, Shenzhen
IP12: Organizer: Qi-Man Shao, Southern University of Science and Technology
Session title: Asymptotic Theory in Probability and Statistics
Chair: Zhuosong Zhang, Southern University of Science and Technology
Speakers:
Lan Gao, University of Tennessee (U.S.)
Shengli Liang, Southern University of Science and Technology
Xiaofan Guo, Southern University of Science and Technology
Songhao Liu Southern University of Science and Technology
IS31: Organizer: Xin Tong, University of Southern California
Session title: Complex Objectives and Data in Statistical Learning
Session chair: Xin Tong, University of Southern California
Speakers:
Jie Hu, Tshinghua University
Xinyue Li, City University of Hong Kong
Qing Yang, University of Science and Technology of China
Xiao Han, University of Science and Technology of China
IS32: Organizer: Bo Zhang, Renmin University of China
Session title：Statistical Inferences on High-frequency Financial Data
Chair: Ben Wu, Renmin University of China
Speakers:
Dachuan Chen，Singapore Management University (Singapore)
Wanwan Liang，Renmin University of China
Zhi Liu, University of Macau
Ben Wu, Renmin University of China
Contributed session
July 8, 8:00-9:50
CS01 Session title: Federated Learning and graph
Chair: Xuejun Jiang, Southern University of Science and Technology, China
Speakers:
1. Ke Deng, Tsinghua University, China, kdeng@tsinghua.edu.cn
2. Yichen Hu, University of California, Davis, U.S.A. ethhu@ucdavis.edu
3. Zhiwei Li, Shanxi University of Finance and Economics, China, lzw_sxufe@163.com
4. Xuejiao Ma, Shanxi University of Finance and Economics, China, 231071400002@stu.sxufe.edu.cn
5. Fan Wang, University of Warwick, fan.wang.4@warwick.ac.uk
6. Weilan Zhang, Shanxi University of Finance and Economics, China, wlzhangtj@163.com
July 8: 10:10-12:00
CS02: Session: Quantile regression and estimating equations
Chair: Ke Deng, Tsinghua University, China
Speakers:
1. Haowen Bao, Chinese Academy of Sciences, bhw@amss.ac.cn
2. Xuejun Jiang, Southern University of Science and Technology, China, jiangxj@sustech.edu.cn
3. Fengying Li, Ningxia Normal University, China, lifengying01@126.com
4. Ruixuan Qin, Xiamen University, China, 1004155560@qq.com
5. Han Yan, Peking University, China, hanyan@stu.pku.edu.cn
6. Tomas Tichy, VSB-TUO, tomas.tichy@vsb.cz
July 8, 14:00-15:50
CS03: Session: .High-dimensional statistical inference
Chair: Xuemei Hu, Chongqing Technology and Business University, China
Speakers:
1. Xiaoyu Hu, National University of Singapore, hxy@nus.edu.sg
2. Hua Li, Chang chun University, China, lihua@ccu.edu.cn
3. Zhangni Pu, Northeast Normal University, China, puzn687@nenu.edu.cn
4. Jiaxin Qiu, The University of Hong Kong, China, qiujx@connect.hku.hk
5. Jingkun Qiu, Peking University, China, jkqiu@stu.pku.edu.cn
6. Hong Wang, Central South University, China, wh@csu.edu.cn
7. Lu Yan, Northeast Normal University, China, yanl129@nenu.edu.cn
July 8: 16:10-18:00
CS04: Session: Longitudinal data and others
Chair: JingkunQiu, Peking University, China
Speakers:
1. Ji Luo, Zhejiang University of Finance and Economics, China, 20000018@zufe.edu.cn
2. Yuanhui Luo, The Hong Kong University of Science and Technology, China, yluocl@connect.ust.hk
3. Guogen Shan, University of Florida, U.S.A., gshan@ufl.edu
4. Cuiling Wang, Albert Einstein College of Medicine, U.S.A. cuiling.wang@einsteinmed.edu
5. Haiyan Yu, Chongqing University of Posts and Telecommunications, China, yhy188@pku.org.cn
6. Baishuai Zuo, Qufu Normal University, China, bszuo124@163.com
July 8: 16:10-18:00
CS05: Session: Finance and econometrics
Chair: Hua Li, Chang chun University, China
Speakers:
1. Xuemei Hu, Chongqing Technology and Business University, China, huxuem@163.com
2. Pingyun Li, Qufu Normal University, China, 995930481@qq.com
3. Tianyi Qu, SF Technology Co., Ltd.; School of Management at Zhejiang University, China, tianyiq1995@163.com
4. Ping Xie, Dalian University of Technology, China, pxiedl@mail.dlut.edu.cn
5. Mengshuo Zhao, Qufu Normal University, China, 571953645@qq.com
6. Pan Zhao, Inria & Université de Montpellier, France, pan.zhao@inria.fr
July 8: 16:10-18:00
CS06: Session: Time series analysis
Chair: Tingting Zou, Jilin University, China
Speakers:
1. Xiao Chen, University of Science and Technology of China, cx990621@mail.ustc.edu.cn
2. Huijie Qiao, Southeast University, China, hjqiaogean@seu.edu.cn
3. Yutong Wu, Ningxia University, China, hbkjwuyutong@163.com
4. Yinghuai Yi, Tsinghua University, China, yyh21@mails.tsinghua.edu.cn
5. Yan Zhang, Xiamen University, China, zhangyan_elyssa@163.com
6. Xinjie Shi, Ningxia University, China, 15065890745@163.com