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Gen Li 0012
Person information
- affiliation: Clemson University, Clemson, SC, USA
Other persons with the same name
- Gen Li — disambiguation page
- Gen Li 0001 — Beijing University of Posts and Telecommunications
- Gen Li 0002 — National University of Defense Technology, Changsha, China
- Gen Li 0003 — Tianjin University, China
- Gen Li 0004
— University of Michigan, Ann Arbor, MI, USA (and 2 more)
- Gen Li 0005 — Chinese University of Hong Kong, Department of Statistics, Hong Kong (and 2 more)
- Gen Li 0006
- Gen Li 0007 — Genetalks Biotech Inc., Beijing, China
- Gen Li 0008
- Gen Li 0009
- Gen Li 0010
- Gen Li 0011
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2020 – today
- 2024
- [c7]Gen Li, Zhihao Shu, Jie Ji, Minghai Qin, Fatemeh Afghah, Wei Niu
Data Overfitting for On-device Super-Resolution with Dynamic Algorithm and Compiler Co-design. ECCV (67) 2024: 360-378 - [c6]Gen Li, Lu Yin, Jie Ji, Wei Niu, Minghai Qin, Bin Ren, Linke Guo, Shiwei Liu, Xiaolong Ma:
NeurRev: Train Better Sparse Neural Network Practically via Neuron Revitalization. ICLR 2024 - [c5]Lu Yin, You Wu, Zhenyu Zhang, Cheng-Yu Hsieh, Yaqing Wang, Yiling Jia, Gen Li, Ajay Kumar Jaiswal, Mykola Pechenizkiy, Yi Liang, Michael Bendersky, Zhangyang Wang, Shiwei Liu:
Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity. ICML 2024 - [c4]Jie Ji, Gen Li, Lu Yin, Minghai Qin, Geng Yuan, Linke Guo, Shiwei Liu, Xiaolong Ma:
Advancing Dynamic Sparse Training by Exploring Optimization Opportunities. ICML 2024 - [c3]Jie Ji, Gen Li, Jingjing Fu, Fatemeh Afghah, Linke Guo, Xiaoyong Yuan, Xiaolong Ma:
A Single-Step, Sharpness-Aware Minimization is All You Need to Achieve Efficient and Accurate Sparse Training. NeurIPS 2024 - [i5]Gen Li, Zhihao Shu, Jie Ji, Minghai Qin, Fatemeh Afghah, Wei Niu
Data Overfitting for On-Device Super-Resolution with Dynamic Algorithm and Compiler Co-Design. CoRR abs/2407.02813 (2024) - [i4]Mingyu Cao, Gen Li, Jie Ji, Jiaqi Zhang, Xiaolong Ma, Shiwei Liu, Lu Yin:
Condense, Don't Just Prune: Enhancing Efficiency and Performance in MoE Layer Pruning. CoRR abs/2412.00069 (2024) - 2023
- [c2]Gen Li, Jie Ji, Minghai Qin, Wei Niu
Towards High-Quality and Efficient Video Super-Resolution via Spatial-Temporal Data Overfitting. CVPR 2023: 10259-10269 - [c1]Lu Yin, Gen Li, Meng Fang, Li Shen, Tianjin Huang, Zhangyang Wang, Vlado Menkovski, Xiaolong Ma, Mykola Pechenizkiy, Shiwei Liu:
Dynamic Sparsity Is Channel-Level Sparsity Learner. NeurIPS 2023 - [i3]Gen Li, Jie Ji, Minghai Qin, Wei Niu
Towards High-Quality and Efficient Video Super-Resolution via Spatial-Temporal Data Overfitting. CoRR abs/2303.08331 (2023) - [i2]Lu Yin, Gen Li, Meng Fang, Li Shen, Tianjin Huang, Zhangyang Wang, Vlado Menkovski, Xiaolong Ma, Mykola Pechenizkiy, Shiwei Liu:
Dynamic Sparsity Is Channel-Level Sparsity Learner. CoRR abs/2305.19454 (2023) - [i1]Yucong Dai, Gen Li, Feng Luo, Xiaolong Ma, Yongkai Wu
Coupling Fairness and Pruning in a Single Run: a Bi-level Optimization Perspective. CoRR abs/2312.10181 (2023)
Coauthor Index
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