About
The TMLR Young Scientist Seminars is an exciting initiative organized by the Trustworthy Machine Learning and Reasoning (TMLR) Group, dedicated to encouraging open discussions, critical thinking, and the exchange of diverse perspectives. This seminar series aims to invite talented young scientists to present their cutting-edge research, exchange ideas, and foster potential collaborations within the vibrant TMLR community.
Video Series
In 2025, we will launch a recording series
Stay tuned
2025
On the origins of linear representations in LLMs
Yibo Jiang (University of Chicago)
6 Oct 2024
On the Landscape of Diffusion Acceleration
Zhengyang Geng (Carnegie Mellon University)
6 Oct 2024
Prompt Injection Defenses by Structured Queries and Alignment Training
Sizhe Chen (University of California, Berkeley)
4 Nov 2024
Building math agent with iterative multi-turn direct preference learning
Wei Xiong (University of Illinois Urbana-Champaign)
11 Nov 2024
Exploring Deep Learning Algorithms: A New Perspective through Feature Learning Theory
Wei Huang (RIKEN AIP)
22 Sep 2023
Upcoming Talks
| Date | Speaker | Topic | Poster |
|---|---|---|---|
| 2025 | Stay tuned (TBD) | TBD | TBD |
Past Talks
| Date | Speaker | Topic | Poster |
|---|---|---|---|
| 6 Oct 2024 | Yibo Jiang (University of Chicago) | On the origins of linear representations in LLMs | View Poster |
| 6 Oct 2024 | Zhengyang Geng (Carnegie Mellon University) | On the Landscape of Diffusion Acceleration | View Poster |
| 4 Nov 2024 | Sizhe Chen (University of California, Berkeley) | Prompt Injection Defenses by Structured Queries and Alignment Training | View Poster |
| 11 Nov 2024 | Wei Xiong (University of Illinois Urbana-Champaign) | Building math agent with iterative multi-turn direct preference learning | View Poster |
| 22 Sep 2023 | Wei Huang (RIKEN AIP) | Exploring Deep Learning Algorithms: A New Perspective through Feature Learning Theory | View Poster |
| 09 Sep 2023 | Junyuan Hong (University of Texas at Austin) | Backdoor Meets Data-Free Learning | View Poster |
| 09 Sep 2023 | Yi Zeng (Virginia Tech) | Data-centric Backdoor Attacks and Countermeasures | View Poster |
| 13 Apr 2023 | Jiaheng Wei (UC Santa Cruz) | Learning with Noisy Labels: Theoretical Approaches and Empirical Studies | View Poster |
| 17 Mar 2023 | Junchi Yu (Chinese Academy of Sciences) | Subgraph-based Trustworthy Graph Learning | View Poster |
| 07 Mar 2023 | Zhuoning Yuan (University of Iowa) | LibAUC: A Deep Learning Library for X-Risk Optimization | View Poster |
| 24 Feb 2023 | Sheng Liu (New York University) | From early-learning to memorization: robust learning via training dynamic | View Poster |
| 19 Jan 2023 | Haibo Yang (Ohio State University) | Towards Efficient Federated Learning: Anytime, Anywhere and with Any Data | View Poster |
| 15 Dec 2022 | Wenxiao Wang (University of Maryland) | Lethal Dose Conjecture: From Few-shot Learning to Potentially Near Optimal Defenses against Data Poisoning | View Poster |
| 9 Sep 2022 | Yaodong Yu (University of California, Berkeley) | Predicting Out-of-Distribution Error with the Projection Norm | View Poster |
| 15 Aug 2022 | Zhiyong Yang (University of Chinese Academy of Sciences) | AUC Optimization under Complex Environment | View Poster |
| 04 Aug 2022 | Weihua Hu (Stanford University) | Learning Backward Compatible Embeddings | View Poster |
| 29 Jun 2022 | Tianlong Chen (University of Texas at Austin) | Finding Good, Cheap, and Transferrable Sparsity: From Fundamental to Advanced Models | View Poster |
Organization Committee
Organization Chairs
Jianing Zhu
Hong Kong Baptist University
Zhanke Zhou
Hong Kong Baptist University
Qizhou Wang
Hong Kong Baptist University
Executive Members
Hongduan Tian
Hong Kong Baptist University
Advisory Board
Jiangchao Yao
Shanghai Jiao Tong University
