Joint Edge-Model Sparse Learning is Provably Efficient for Graph Neural Networks
- Shuai Zhang
- Meng Weng
- et al.
- 2023
- ICLR 2023
Conference paper
Publications
32 results for Sijia Liu
A Theoretical Understanding of Shallow Vision Transformers: Learning, Generalization, and Sample Complexity
- Hongkang Li
- Meng Weng
- et al.
- 2023
- ICLR 2023
Conference paperVisual Prompting for Adversarial Robustness
- Aochuan Chen
- Peter Lorenz
- et al.
- 2022
- NeurIPS 2022
Workshop paperFoundational Robustness of Foundation Models
- Pin-Yu Chen
- Sijia Liu
- et al.
- 2022
- NeurIPS 2022
TutorialData-Efficient Double-Win Lottery Tickets from Robust Pre-training
- Tianlong Chen
- Zhenyu Zhang
- et al.
- 2022
- ICML 2022
Conference paperNew Frontiers in Adversarial Machine Learning
- Sijia Liu
- Pin-Yu Chen
- et al.
- 2022
- ICML 2022
WorkshopHow unlabeled data improve generalization in self-training? A one-hidden-layer theoretical analysis
- Shuai Zhang
- Meng Weng
- et al.
- 2022
- ICLR 2022
Conference paperWhy Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Sparse Neural Networks
- Shuai Zhang
- Meng Weng
- et al.
- 2021
- NeurIPS 2021
Conference paperWhen does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning?
- Lijie Fan
- Sijia Liu
- et al.
- 2021
- NeurIPS 2021
Conference paperMEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge
- Geng Yuan
- Xialong Ma
- et al.
- 2021
- NeurIPS 2021
Conference paper