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ORCIDDa Li 0001
Person information
- affiliation: Samsung AI Centre, Cambridge, UK
- affiliation: University of Edinburgh, School of Informatics, UK
- affiliation: Queen Mary University of London, UK
- affiliation: University of Surrey, SketchX Laboratory, Guildford, UK
Other persons with the same name
- Da Li — disambiguation page
- Da Li 0002 — Facebook Inc. (and 1 more)
- Da Li 0003
![[0000-0001-6822-3989]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0001-6822-3989")
— University of Chinese Academy of Sciences (UCAS), School of Artificial Intelligence, Beijing, China (and 1 more) - Da Li 0004 — Beijing University of Technology, Embedded Software and Systems Institute, China (and 1 more)
- Da Li 0005 — National University of Defense Technology, School of Electronic Countermeasures, Hefei, China
- Da Li 0006 — Northwest Institute of Eco-Environment and Resources, State Key Laboratory of Cryospheric Science Lanzhou, China
- Da Li 0007 — Wuhan University of Technology, School of Information Engineering, China (and 2 more)
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2020 – today
- 2024
[c28]Panagiotis Eustratiadis, Lukasz Dudziak, Da Li, Timothy M. Hospedales:
Neural Fine-Tuning Search for Few-Shot Learning. ICLR 2024- [c27]Royson Lee, Javier Fernández-Marqués, Shell Xu Hu, Da Li, Stefanos Laskaridis, Lukasz Dudziak, Timothy M. Hospedales, Ferenc Huszár, Nicholas Donald Lane:
Recurrent Early Exits for Federated Learning with Heterogeneous Clients. ICML 2024 - [c26]Ondrej Bohdal, Da Li, Shell Xu Hu, Timothy M. Hospedales:
Feed-Forward Latent Domain Adaptation. WACV 2024: 8475-8484 - [i33]Royson Lee, Javier Fernández-Marqués, Shell Xu Hu, Da Li, Stefanos Laskaridis, Lukasz Dudziak, Timothy M. Hospedales, Ferenc Huszár, Nicholas D. Lane:
Recurrent Early Exits for Federated Learning with Heterogeneous Clients. CoRR abs/2405.14791 (2024) - [i32]Ruchika Chavhan, Da Li, Timothy M. Hospedales:
ConceptPrune: Concept Editing in Diffusion Models via Skilled Neuron Pruning. CoRR abs/2405.19237 (2024) - [i31]Ruchika Chavhan, Ondrej Bohdal, Yongshuo Zong, Da Li, Timothy M. Hospedales:
Memorized Images in Diffusion Models share a Subspace that can be Located and Deleted. CoRR abs/2406.18566 (2024) - 2023
- [j5]Zhihe Lu, Sen He, Da Li, Yi-Zhe Song, Tao Xiang:
Prediction Calibration for Generalized Few-Shot Semantic Segmentation. IEEE Trans. Image Process. 32: 3311-3323 (2023) - [j4]Zhihe Lu, Da Li, Yi-Zhe Song, Tao Xiang, Timothy M. Hospedales:
Uncertainty-Aware Source-Free Domain Adaptive Semantic Segmentation. IEEE Trans. Image Process. 32: 4664-4676 (2023) - [j3]Jingshi Lei, Da Li, Chengming Xu, Liming Fang, Timothy M. Hospedales, Yanwei Fu:
Worst-case Feature Risk Minimization for Data-Efficient Learning. Trans. Mach. Learn. Res. 2023 (2023) - [c25]Linus Ericsson, Da Li, Timothy M. Hospedales:
Better Practices for Domain Adaptation. AutoML 2023: 4/1-25 - [c24]Ruolin Yang, Da Li, Conghui Hu, Timothy M. Hospedales, Honggang Zhang, Yi-Zhe Song:
Sketch-based Video Object Segmentation: Benchmark and Analysis. BMVC 2023: 540-541 - [c23]Ondrej Bohdal, Yinbing Tian, Yongshuo Zong, Ruchika Chavhan, Da Li, Henry Gouk, Li Guo, Timothy M. Hospedales:
Meta Omnium: A Benchmark for General-Purpose Learning-to-Learn. CVPR 2023: 7693-7703 - [c22]Fengyin Lin, Mingkang Li, Da Li, Timothy M. Hospedales, Yi-Zhe Song, Yonggang Qi:
Zero-Shot Everything Sketch-Based Image Retrieval, and in Explainable Style. CVPR 2023: 23349-23358 - [c21]Ruchika Chavhan, Henry Gouk, Da Li, Timothy M. Hospedales:
Quality Diversity for Visual Pre-Training. ICCV 2023: 5361-5371 - [c20]Minyoung Kim, Da Li, Timothy M. Hospedales:
Domain Generalisation via Domain Adaptation: An Adversarial Fourier Amplitude Approach. ICLR 2023 - [c19]Qiang Wang, Haoge Deng, Yonggang Qi, Da Li, Yi-Zhe Song:
SketchKnitter: Vectorized Sketch Generation with Diffusion Models. ICLR 2023 - [c18]Royson Lee, Minyoung Kim, Da Li, Xinchi Qiu, Timothy M. Hospedales, Ferenc Huszar, Nicholas D. Lane:
FedL2P: Federated Learning to Personalize. NeurIPS 2023 - [i30]Minyoung Kim, Da Li, Timothy M. Hospedales:
Domain Generalisation via Domain Adaptation: An Adversarial Fourier Amplitude Approach. CoRR abs/2302.12047 (2023) - [i29]Zhongying Deng, Da Li, Junjun He, Yi-Zhe Song, Tao Xiang:
Generative Model Based Noise Robust Training for Unsupervised Domain Adaptation. CoRR abs/2303.05734 (2023) - [i28]Fengyin Lin, Mingkang Li, Da Li, Timothy M. Hospedales, Yi-Zhe Song, Yonggang Qi:
Zero-Shot Everything Sketch-Based Image Retrieval, and in Explainable Style. CoRR abs/2303.14348 (2023) - [i27]Ondrej Bohdal, Yinbing Tian, Yongshuo Zong, Ruchika Chavhan, Da Li, Henry Gouk, Li Guo, Timothy M. Hospedales:
Meta Omnium: A Benchmark for General-Purpose Learning-to-Learn. CoRR abs/2305.07625 (2023) - [i26]Panagiotis Eustratiadis, Lukasz Dudziak, Da Li, Timothy M. Hospedales:
Neural Fine-Tuning Search for Few-Shot Learning. CoRR abs/2306.09295 (2023) - [i25]Ondrej Bohdal, Da Li, Timothy M. Hospedales:
Feed-Forward Source-Free Domain Adaptation via Class Prototypes. CoRR abs/2307.10787 (2023) - [i24]Ondrej Bohdal, Da Li, Timothy M. Hospedales:
Label Calibration for Semantic Segmentation Under Domain Shift. CoRR abs/2307.10842 (2023) - [i23]Linus Ericsson, Da Li, Timothy M. Hospedales:
Better Practices for Domain Adaptation. CoRR abs/2309.03879 (2023) - [i22]Royson Lee, Minyoung Kim, Da Li, Xinchi Qiu, Timothy M. Hospedales, Ferenc Huszár, Nicholas D. Lane:
FedL2P: Federated Learning to Personalize. CoRR abs/2310.02420 (2023) - [i21]Ruolin Yang, Da Li, Conghui Hu, Timothy M. Hospedales, Honggang Zhang, Yi-Zhe Song:
Sketch-based Video Object Segmentation: Benchmark and Analysis. CoRR abs/2311.07261 (2023) - 2022
- [j2]Zhongying Deng, Kaiyang Zhou, Da Li, Junjun He, Yi-Zhe Song, Tao Xiang:
Dynamic Instance Domain Adaptation. IEEE Trans. Image Process. 31: 4585-4597 (2022) - [c17]Zhongying Deng, Da Li, Yi-Zhe Song, Tao Xiang:
Robust Target Training for Multi-Source Domain Adaptation. BMVC 2022: 778 - [c16]Tingwei Wang, Da Li, Kaiyang Zhou, Tao Xiang, Yi-Zhe Song:
Learning to Augment via Implicit Differentiation for Domain Generalization. BMVC 2022: 888 - [c15]Shell Xu Hu, Da Li, Jan Stühmer, Minyoung Kim, Timothy M. Hospedales:
Pushing the Limits of Simple Pipelines for Few-Shot Learning: External Data and Fine-Tuning Make a Difference. CVPR 2022: 9058-9067 - [c14]Minyoung Kim, Da Li, Shell Xu Hu, Timothy M. Hospedales:
Fisher SAM: Information Geometry and Sharpness Aware Minimisation. ICML 2022: 11148-11161 - [i20]Da Li, Henry Gouk, Timothy M. Hospedales:
Finding lost DG: Explaining domain generalization via model complexity. CoRR abs/2202.00563 (2022) - [i19]Zhongying Deng, Kaiyang Zhou, Da Li, Junjun He, Yi-Zhe Song, Tao Xiang:
Dynamic Instance Domain Adaptation. CoRR abs/2203.05028 (2022) - [i18]Shell Xu Hu, Da Li, Jan Stühmer, Minyoung Kim, Timothy M. Hospedales:
Pushing the Limits of Simple Pipelines for Few-Shot Learning: External Data and Fine-Tuning Make a Difference. CoRR abs/2204.07305 (2022) - [i17]Minyoung Kim, Da Li, Shell Xu Hu, Timothy M. Hospedales:
Fisher SAM: Information Geometry and Sharpness Aware Minimisation. CoRR abs/2206.04920 (2022) - [i16]Ondrej Bohdal, Da Li, Shell Xu Hu, Timothy M. Hospedales:
Feed-Forward Source-Free Latent Domain Adaptation via Cross-Attention. CoRR abs/2207.07624 (2022) - [i15]Ke Fan, Yikai Wang, Qian Yu, Da Li, Yanwei Fu:
A Simple Test-Time Method for Out-of-Distribution Detection. CoRR abs/2207.08210 (2022) - [i14]Panagiotis Eustratiadis, Henry Gouk, Da Li, Timothy M. Hospedales:
Attacking Adversarial Defences by Smoothing the Loss Landscape. CoRR abs/2208.00862 (2022) - [i13]Zhongying Deng, Da Li, Yi-Zhe Song, Tao Xiang:
Robust Target Training for Multi-Source Domain Adaptation. CoRR abs/2210.01676 (2022) - [i12]Zhihe Lu, Sen He, Da Li, Yi-Zhe Song, Tao Xiang:
Prediction Calibration for Generalized Few-shot Semantic Segmentation. CoRR abs/2210.08290 (2022) - [i11]Tingwei Wang, Da Li, Kaiyang Zhou, Tao Xiang, Yi-Zhe Song:
Learning to Augment via Implicit Differentiation for Domain Generalization. CoRR abs/2210.14271 (2022) - [i10]Zicheng Liu, Da Li, Javier Fernández-Marqués, Stefanos Laskaridis, Yan Gao, Lukasz Dudziak, Stan Z. Li, Shell Xu Hu, Timothy M. Hospedales:
Federated Learning for Inference at Anytime and Anywhere. CoRR abs/2212.04084 (2022) - 2021
- [c13]Tianyuan Yu, Yongxin Yang, Da Li, Timothy M. Hospedales, Tao Xiang:
Simple and Effective Stochastic Neural Networks. AAAI 2021: 3252-3260 - [c12]Pan Li, Da Li, Wei Li, Shaogang Gong, Yanwei Fu, Timothy M. Hospedales:
A Simple Feature Augmentation for Domain Generalization. ICCV 2021: 8866-8875 - [c11]Panagiotis Eustratiadis, Henry Gouk, Da Li, Timothy M. Hospedales:
Weight-covariance alignment for adversarially robust neural networks. ICML 2021: 3047-3056 - [c10]Rui Li, Ondrej Bohdal, Rajesh K. Mishra, Hyeji Kim, Da Li, Nicholas D. Lane, Timothy M. Hospedales:
A Channel Coding Benchmark for Meta-Learning. NeurIPS Datasets and Benchmarks 2021 - [i9]Rui Li, Ondrej Bohdal, Rajesh K. Mishra, Hyeji Kim, Da Li, Nicholas D. Lane, Timothy M. Hospedales:
A Channel Coding Benchmark for Meta-Learning. CoRR abs/2107.07579 (2021) - 2020
- [j1]Conghui Hu, Da Li, Yongxin Yang, Timothy M. Hospedales, Yi-Zhe Song:
Sketch-a-Segmenter: Sketch-Based Photo Segmenter Generation. IEEE Trans. Image Process. 29: 9470-9481 (2020) - [c9]Da Li, Timothy M. Hospedales:
Online Meta-learning for Multi-source and Semi-supervised Domain Adaptation. ECCV (16) 2020: 382-403 - [c8]Da Li, Yongxin Yang, Yi-Zhe Song, Timothy M. Hospedales:
Sequential Learning for Domain Generalization. ECCV Workshops (1) 2020: 603-619 - [i8]Da Li, Yongxin Yang, Yi-Zhe Song, Timothy M. Hospedales:
Sequential Learning for Domain Generalization. CoRR abs/2004.01377 (2020) - [i7]Da Li, Timothy M. Hospedales:
Online Meta-Learning for Multi-Source and Semi-Supervised Domain Adaptation. CoRR abs/2004.04398 (2020) - [i6]Panagiotis Eustratiadis, Henry Gouk, Da Li, Timothy M. Hospedales:
A Stochastic Neural Network for Attack-Agnostic Adversarial Robustness. CoRR abs/2010.08852 (2020)
2010 – 2019
- 2019
- [c7]Tianyuan Yu, Da Li, Yongxin Yang, Timothy M. Hospedales, Tao Xiang:
Robust Person Re-Identification by Modelling Feature Uncertainty. ICCV 2019: 552-561 - [c6]Da Li, Jianshu Zhang, Yongxin Yang, Cong Liu, Yi-Zhe Song, Timothy M. Hospedales:
Episodic Training for Domain Generalization. ICCV 2019: 1446-1455 - [i5]Da Li, Jianshu Zhang, Yongxin Yang, Cong Liu, Yi-Zhe Song, Timothy M. Hospedales:
Episodic Training for Domain Generalization. CoRR abs/1902.00113 (2019) - 2018
- [c5]Da Li, Yongxin Yang, Yi-Zhe Song, Timothy M. Hospedales:
Learning to Generalize: Meta-Learning for Domain Generalization. AAAI 2018: 3490-3497 - [c4]Conghui Hu, Da Li, Yi-Zhe Song, Tao Xiang, Timothy M. Hospedales:
Sketch-a-Classifier: Sketch-Based Photo Classifier Generation. CVPR 2018: 9136-9144 - [c3]Kaiyue Pang, Da Li, Jifei Song, Yi-Zhe Song, Tao Xiang, Timothy M. Hospedales:
Deep Factorised Inverse-Sketching. ECCV (15) 2018: 37-54 - [i4]Conghui Hu, Da Li, Yi-Zhe Song, Tao Xiang, Timothy M. Hospedales:
Sketch-a-Classifier: Sketch-based Photo Classifier Generation. CoRR abs/1804.11182 (2018) - [i3]Kaiyue Pang, Da Li, Jifei Song, Yi-Zhe Song, Tao Xiang, Timothy M. Hospedales:
Deep Factorised Inverse-Sketching. CoRR abs/1808.02313 (2018) - 2017
- [c2]Conghui Hu, Da Li, Yi-Zhe Song, Timothy M. Hospedales:
Now You See Me: Deep Face Hallucination for Unviewed Sketches. BMVC 2017 - [c1]Da Li, Yongxin Yang, Yi-Zhe Song, Timothy M. Hospedales:
Deeper, Broader and Artier Domain Generalization. ICCV 2017: 5543-5551 - [i2]Da Li, Yongxin Yang, Yi-Zhe Song, Timothy M. Hospedales:
Deeper, Broader and Artier Domain Generalization. CoRR abs/1710.03077 (2017) - [i1]Da Li, Yongxin Yang, Yi-Zhe Song, Timothy M. Hospedales:
Learning to Generalize: Meta-Learning for Domain Generalization. CoRR abs/1710.03463 (2017)
Coauthor Index
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