Welcome to the website of the Learning and INference Systems (LINs) Lab at Westlake University!
Our research interests lie in the intersection of optimization and generalization for deep learning:
- leveraging theoretical/empirical understanding (e.g., loss landscape, and training dynamics)
- to design efficient & robust methods (both learning and inference)
- for deep learning (centralized) and collaborative deep learning (distributed and/or decentralized),
- under imperfect environments (e.g., noisy, heterogeneous, and hardware-constrained).
Lab activities:
- We are running a research seminar on Deep Learning and Optimization.
News
| Sep 27, 2024 | Two papers of our group were accepted at this year’s NeurIPS 2024 conference. Congratulations to Peng on the acceptance of his paper on Ideal Data, and congratulations to Jiamin for his attempts on Cooperative Hardware-Prompt Learning. |
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| Jul 2, 2024 | Congratulations to Yuxuan on the oral acceptance of his paper on multimodal benchmark in pathology at ECCV 2024. This paper was selected as the one of best paper candidates at ECCV. |
| May 2, 2024 | Our paper on distribution-shift-robust Federated Learning was accepted at this year’s ICML 2024 conference. Congratulations to Yongxin. |
| Feb 27, 2024 | Our paper on efficient dataset distillation was accepted at this year’s CVPR 2024 conference. Congratulations to Peng (he also received a CVPR 2024 travel grant). |
| Feb 4, 2024 | We are looking for self-motivated research internship students! Please email us with your CV. |