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ORCIDYao Li 0015
Person information
- unicode name: 李垚
- affiliation: University of North Carolina at Chapel Hill, Department of Statistics and Operation Research, NC, USA
- affiliation (PhD 2020): University of California, Davis, Department of Statistics, CA, USA
Other persons with the same name
- Yao Li — disambiguation page
- Yao Li 0001 — Carleton University, Telecommunications Research Institute of Ontario, Ottawa, Canada
- Yao Li 0002 — Huazhong University of Science and Technology, China
- Yao Li 0003 — University of Adelaide, School of Computer Science, Australia
- Yao Li 0004
![[0000-0001-8720-883X]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0001-8720-883X")
— University of Pennsylvania, Department of Computer and Information Science, Philadelphia, PA, USA (and 2 more) - Yao Li 0005 — Southeast University, MOE Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology, Nanjing, China
- Yao Li 0006 — University of California, Irvine, Irvine, CA, USA
- Yao Li 0007 — Akamai Technologies, Inc., Santa Clara, CA, USA (and 2 more)
- Yao Li 0008 — University of Maryland, Baltimore County, Baltimore, MD, USA
- Yao Li 0009 — Université Pierre et Marie Curie, Paris, France
- Yao Li 0010 — Shanghai Jiao Tong University, School of Biomedical Engineering, China
- Yao Li 0011 — ZheJiang Sci-Tech University, School of Information Science and Technology, Hangzhou, China
- Yao Li 0012 — Northeastern University, Shenyang, China
- Yao Li 0013 — Chinese Academy of Sciences, Key Laboratory of Mountain Hazards and Earth Surface Process, Chengdu, China
- Yao Li 0014 — Harbin Institute of Technology, State Key Laboratory of Robotics and System, China
- Yao Li 0016 — University of Science and Technology of China, School of Computer Science and Technology, Hefei, China
- Yao Li 0017 — Macau University of Science and Technology (MUST), School of Computer Science and Technology, Taipa, Macau
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2020 – today
- 2024
[j3]Xiawei Wang, Yao Li, Cho-Jui Hsieh, Thomas C. M. Lee:
Uncovering Distortion Differences: A Study of Adversarial Attacks and Machine Discriminability. IEEE Access 12: 117872-117883 (2024)- [j2]Yao Li, Tongyi Tang, Cho-Jui Hsieh, Thomas C. M. Lee:
Adversarial Examples Detection With Bayesian Neural Network. IEEE Trans. Emerg. Top. Comput. Intell. 8(5): 3654-3664 (2024) - [c9]Shengkun Tang, Yaqing Wang, Caiwen Ding, Yi Liang, Yao Li, Dongkuan Xu:
AdaDiff: Accelerating Diffusion Models Through Step-Wise Adaptive Computation. ECCV (79) 2024: 73-90 - [c8]Cong Zeng, Shengkun Tang, Xianjun Yang, Yuanzhou Chen, Yiyou Sun, Zhiqiang Xu, Yao Li, Haifeng Chen, Wei Cheng, Dongkuan Xu:
DALD: Improving Logits-based Detector without Logits from Black-box LLMs. NeurIPS 2024 - [i11]Cong Zeng, Shengkun Tang, Xianjun Yang, Yuanzhou Chen, Yiyou Sun, Zhiqiang Xu, Yao Li, Haifeng Chen, Wei Cheng, Dongkuan Xu:
Improving Logits-based Detector without Logits from Black-box LLMs. CoRR abs/2406.05232 (2024) - [i10]Xinglin Li, Xianwen He, Yao Li, Minhao Cheng:
Defense Against Syntactic Textual Backdoor Attacks with Token Substitution. CoRR abs/2407.04179 (2024) - 2023
- [c7]Shengkun Tang, Yaqing Wang, Zhenglun Kong, Tianchi Zhang, Yao Li, Caiwen Ding, Yanzhi Wang, Yi Liang, Dongkuan Xu:
You Need Multiple Exiting: Dynamic Early Exiting for Accelerating Unified Vision Language Model. CVPR 2023: 10781-10791 - [c6]Lei Zhang, Jie Zhang, Bowen Lei, Subhabrata Mukherjee, Xiang Pan, Bo Zhao, Caiwen Ding, Yao Li, Dongkuan Xu:
Accelerating Dataset Distillation via Model Augmentation. CVPR 2023: 11950-11959 - [i9]Shengkun Tang, Yaqing Wang, Caiwen Ding, Yi Liang, Yao Li, Dongkuan Xu:
DeeDiff: Dynamic Uncertainty-Aware Early Exiting for Accelerating Diffusion Model Generation. CoRR abs/2309.17074 (2023) - 2022
- [c5]Fan Yin, Yao Li, Cho-Jui Hsieh, Kai-Wei Chang:
ADDMU: Detection of Far-Boundary Adversarial Examples with Data and Model Uncertainty Estimation. EMNLP 2022: 6567-6584 - [i8]Fan Yin, Yao Li, Cho-Jui Hsieh, Kai-Wei Chang:
ADDMU: Detection of Far-Boundary Adversarial Examples with Data and Model Uncertainty Estimation. CoRR abs/2210.12396 (2022) - [i7]Shengkun Tang, Yaqing Wang, Zhenglun Kong, Tianchi Zhang, Yao Li, Caiwen Ding, Yanzhi Wang, Yi Liang, Dongkuan Xu:
You Need Multiple Exiting: Dynamic Early Exiting for Accelerating Unified Vision Language Model. CoRR abs/2211.11152 (2022) - [i6]Lei Zhang, Jie Zhang, Bowen Lei, Subhabrata Mukherjee, Xiang Pan, Bo Zhao, Caiwen Ding, Yao Li, Dongkuan Xu:
Accelerating Dataset Distillation via Model Augmentation. CoRR abs/2212.06152 (2022) - 2021
- [c4]Yao Li, Martin Renqiang Min, Thomas C. M. Lee, Wenchao Yu, Erik Kruus, Wei Wang, Cho-Jui Hsieh:
Towards Robustness of Deep Neural Networks via Regularization. ICCV 2021: 7476-7485 - [i5]Yao Li, Tongyi Tang, Cho-Jui Hsieh, Thomas C. M. Lee:
Detecting Adversarial Examples with Bayesian Neural Network. CoRR abs/2105.08620 (2021) - [i4]Yao Li, Minhao Cheng, Cho-Jui Hsieh, Thomas C. M. Lee:
A Review of Adversarial Attack and Defense for Classification Methods. CoRR abs/2111.09961 (2021) - 2020
- [j1]Qi Gao, Randy C. S. Lai, Thomas C. M. Lee, Yao Li:
Uncertainty Quantification for High-Dimensional Sparse Nonparametric Additive Models. Technometrics 62(4): 513-524 (2020)
2010 – 2019
- 2019
- [c3]Xuanqing Liu, Yao Li, Chongruo Wu, Cho-Jui Hsieh:
Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network. ICLR (Poster) 2019 - 2018
- [c2]Yao Li, Minhao Cheng, Kevin Fujii, Fushing Hsieh, Cho-Jui Hsieh:
Learning from Group Comparisons: Exploiting Higher Order Interactions. NeurIPS 2018: 4986-4995 - [i3]Xuanqing Liu, Yao Li, Chongruo Wu, Cho-Jui Hsieh:
Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network. CoRR abs/1810.01279 (2018) - [i2]Yao Li, Martin Renqiang Min, Wenchao Yu, Cho-Jui Hsieh, Thomas C. M. Lee, Erik Kruus:
Optimal Transport Classifier: Defending Against Adversarial Attacks by Regularized Deep Embedding. CoRR abs/1811.07950 (2018) - 2017
- [c1]Jinfeng Yi, Cho-Jui Hsieh, Kush R. Varshney, Lijun Zhang, Yao Li:
Scalable Demand-Aware Recommendation. NIPS 2017: 2412-2421 - [i1]Jinfeng Yi, Cho-Jui Hsieh, Kush R. Varshney, Lijun Zhang, Yao Li:
Positive-Unlabeled Demand-Aware Recommendation. CoRR abs/1702.06347 (2017)
Coauthor Index
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