编号 | 时间 | 类型 | 题目 | 讲者 | 单位 |
---|---|---|---|---|---|
1 | 10:30-10:55 | 邀请报告 |
Optimal Clustering by Lloyd Algorithm for Low-Rank Mixture Model |
Dong Xia | Hong Kong University of Science and Technology |
2 | 10:55-11:20 | 邀请报告 |
Rising Ownership Network in China |
祝 武 | 清华大学经管学院 |
3 | 11:20-11:45 | 邀请报告 |
Network Regression and Supervised Centrality Estimation |
Dan Yang | The University of Hong Kong |
4 | 11:45-12:10 | 邀请报告 |
A Joint Estimation Approach to Sparse Additive Ordinary Differential Equations |
张 楠 | 复旦大学 |
编号 | 时间 | 类型 | 题目 | 讲者 | 单位 |
---|---|---|---|---|---|
1 | 14:00-14:25 | 邀请报告 |
Regularized Multi-output Gaussian Convolution Process with Domain Adaptation |
吴建国 | 北京大学 |
2 | 14:25-14:50 | 邀请报告 |
Thompson Sampling based Partially Observable Online Change Detection for Exponential Families |
张 晨 | 清华大学 |
3 | 14:50-15:15 | 邀请报告 |
Harnessing Industrial Analytics and Intelligence for Digital Transformation |
宗福季 | HKUST(GZ) |
4 | 15:15-15:40 | 邀请报告 |
Lattice-based designs possessing quasi-optimal separation distance on all projections |
何 煦 | 中国科学院数学与系统科学研究院 |
编号 | 时间 | 类型 | 题目 | 讲者 | 单位 |
---|---|---|---|---|---|
1 | 16:00-16:25 | 邀请报告 |
Test-Then-Pool: A uniformly valid inferential framework for data integration |
Shu Yang | North Carolina State University |
2 | 16:25-16:50 | 邀请报告 |
Inference of Heterogeneous Treatment Effects Using Observational Data with High-Dimensional Covariates |
邱宇谋 | 北京大学 |
3 | 16:50-17:15 | 邀请报告 |
ELSA: Efficient Label Shift Adaptation through the Lens of Semiparametric Models |
Jiwei Zhao | University of Wisconsin-Madison |
4 | 17:15-17:40 | 邀请报告 |
Semiparametric adaptive estimation under informative sampling |
Kosuke Morikawa | Osaka University |