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  • 香港中文大学戴奔博士:Significance tests of feature relevance for a black-box learner
  • 湘潭大学向开南教授:极小生成森林中树的数目
  • 上海财经大学贺莘副教授:Learning linear non-Gaussian directed acyclic graph: From single to multiple sources
  • 上海财经大学周帆副教授:Recent advances in Distributional Reinforcement Learning
  • 上海财经大学邱怡轩教授:A Semi-smooth, Self-shifting, and Singular Newton Method for Sparse Optimal Transport
  • 上海财经大学冯兴东教授:Deep Over-parameterized Smoothing Quantile Regression
  • 美国密歇根大学宋学坤教授:Identification of Chang-points in Scalar-on-Function Regression
  • 加州大学伯克利分校丁鹏副教授:Causal inference in network experiments: regression-based analysis and design-based properties
  • 华东师范大学唐炎林教授:Distribution-free prediction bands for clustered data with missing responses
  • 圣路易斯华盛顿大学林楠教授:Sure independence screening for mediation analysis
  • 清华大学侯琳副教授:Bayesian regression approach for polygenic risk prediction
  • 中山大学蒋智超教授:An instrumental variable method for point processes
  • 北京师范大学郭旭教授:Test and Measure for Partial Mean Dependence Based on Machine Learning Methods
  • 香港理工大学赵兴球教授:Deep Nonparametric Inference for Conditional Hazard Function
  • 香港理工大学黄坚教授:Conditional Stochastic Interpolation for Generative Learning
  • 罗格斯大学Cun-Hui Zhang教授: Statistical Inference in High-Dimensional Problems
  • 中国科学院数学与系统科学研究院张维副研究员:Optimizing treatment allocation in randomized clinical trials by leveraging baseline covariates
  • 加拿大约克大学吴月华教授:A general latent dimension estimation method for nonstationary processes
  • 罗格斯大学谢敏革(Min-ge Xie )教授:Repro Samples Method for Irregular Inference Problems and for Unraveling Machine Learning Blackboxes
  • 清华大学王天颖助理教授:A unified quantile framework reveals nonlinear heterogeneous transcriptome-wide associations