编号 | 时间 | 类型 | 题目 | 讲者 | 单位 |
---|---|---|---|---|---|
1 | 08:30-08:55 | 邀请报告 |
Privacy-Preserving Community Detection for Locally Distributed Multiple Networks |
Shujie Ma | University of California, Riverside |
2 | 08:55-09:20 | 邀请报告 |
Dynamic Models Augmented by Hierarchical Data |
Le Bao | The Pennsylvania State University |
3 | 09:20-09:45 | 邀请报告 |
An SPDE Approach to Variational Inference for Log-Gaussian Cox Process |
张楠 | 复旦大学 |
编号 | 时间 | 类型 | 题目 | 讲者 | 单位 |
---|---|---|---|---|---|
1 | 10:30-10:55 | 邀请报告 |
Learning from Vertically Distributed Data across Multiple Sites: An Efficient Privacy-Preserving Algorithm for Cox Proportional Hazards Model with Variable Selection |
Samuel Wu | University of Florida |
2 | 10:55-11:20 | 邀请报告 |
New Composite Score to Detect Disease Progression in Alzheimer's Disease |
Guogen Shan | University of Florida |
3 | 11:20-11:45 | 邀请报告 |
Differentially Private Data Collection with Matrix Masking |
Adam Ding | Northeastern University |
4 | 11:45-12:10 | 邀请报告 |
Joint Modeling in Presence of Informative Censoring on the Retrospective Time Scale with Application to Palliative Care Research |
Zhigang Li | University of Florida |
编号 | 时间 | 类型 | 题目 | 讲者 | 单位 |
---|---|---|---|---|---|
1 | 14:00-14:20 | 贡献报告 |
Model Averaging Based Semiparametric Modelling for Conditional Quantile Prediction |
郭朝会 | 重庆师范大学 |
2 | 14:20-14:40 | 贡献报告 |
Bootstrapping the Double-Weighted Predictability Test for Predictive Quantile Regression |
刘小惠 | 江西财经大学 |
3 | 14:40-15:00 | 贡献报告 |
Recent Developments of A General Minimum Lower-Order Confounding Criterion |
李智明 | 新疆大学 |
4 | 15:00-15:20 | 贡献报告 |
Enhancing the Power of OOD Detection via Sample-Aware Model Selection |
谭发龙 | 湖南大学 |
5 | 15:20-15:40 | 贡献报告 |
Unconditional Quantile Regression for Streaming Data Sets |
姜荣 | 上海第二工业大学 |
编号 | 时间 | 类型 | 题目 | 讲者 | 单位 |
---|---|---|---|---|---|
1 | 16:00-16:20 | 贡献报告 |
Shupai Big Model Platform (A Large Model Platform Based on Ai Computing Power Management, Helping You Create Private Large Models In 30 Minutes) 数派大模型平台(一款基于基于AI算力管理的大模型平台,帮您30分钟创建私有大模型) |
廖结义 | 云南数派数据科技有限公司 |
2 | 16:20-16:40 | 贡献报告 |
Computing Power Drive, Data Empowerment, Build a New Pattern of Digital Economy Development 算力驱动,数据赋能,构建数字经济发展新格局 |
Qiqiang Fan | Yunnan Provincial Digital Economy Industry Investment Group Co., Ltd |
3 | 16:40-17:00 | 贡献报告 |
Application Practice and Reflection of Artificial Intelligence Technology in Life Sciences 人工智能技术在生命科学的应用实践及思考 |
高跃东 | 中国科学院昆明动物研究所 |
4 | 17:00-17:20 | 贡献报告 |
Industry Empowerment Based on the Nine Day Model 基于九天大模型的行业赋能 |
燕晨 | 中国移动通信研究院 |
5 | 17:20-17:40 | 贡献报告 |
Ascending AI Accelerates the Deepening of Artificial Intelligence Towards Reality 昇腾AI加速人工智能走深向实 |
杨志鹏 | 华为云南 |